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Sample records for atlas tdaq network

  1. System administration of ATLAS TDAQ computing environment

    Science.gov (United States)

    Adeel-Ur-Rehman, A.; Bujor, F.; Benes, J.; Caramarcu, C.; Dobson, M.; Dumitrescu, A.; Dumitru, I.; Leahu, M.; Valsan, L.; Oreshkin, A.; Popov, D.; Unel, G.; Zaytsev, A.

    2010-04-01

    This contribution gives a thorough overview of the ATLAS TDAQ SysAdmin group activities which deals with administration of the TDAQ computing environment supporting High Level Trigger, Event Filter and other subsystems of the ATLAS detector operating on LHC collider at CERN. The current installation consists of approximately 1500 netbooted nodes managed by more than 60 dedicated servers, about 40 multi-screen user interface machines installed in the control rooms and various hardware and service monitoring machines as well. In the final configuration, the online computer farm will be capable of hosting tens of thousands applications running simultaneously. The software distribution requirements are matched by the two level NFS based solution. Hardware and network monitoring systems of ATLAS TDAQ are based on NAGIOS and MySQL cluster behind it for accounting and storing the monitoring data collected, IPMI tools, CERN LANDB and the dedicated tools developed by the group, e.g. ConfdbUI. The user management schema deployed in TDAQ environment is founded on the authentication and role management system based on LDAP. External access to the ATLAS online computing facilities is provided by means of the gateways supplied with an accounting system as well. Current activities of the group include deployment of the centralized storage system, testing and validating hardware solutions for future use within the ATLAS TDAQ environment including new multi-core blade servers, developing GUI tools for user authentication and roles management, testing and validating 64-bit OS, and upgrading the existing TDAQ hardware components, authentication servers and the gateways.

  2. Quality of service on Linux for the Atlas TDAQ event building network

    International Nuclear Information System (INIS)

    Yasu, Y.; Manabe, A.; Fujii, H.; Watase, Y.; Nagasaka, Y.; Hasegawa, Y.; Shimojima, M.; Nomachi, M.

    2001-01-01

    Congestion control for packets sent on a network is important for DAQ systems that contain an event builder using switching network technologies. Quality of Service (QoS) is a technique for congestion control. Recent Linux releases provide QoS in the kernel to manage network traffic. The authors have analyzed the packet-loss and packet distribution for the event builder prototype of the Atlas TDAQ system. The authors used PC/Linux with Gigabit Ethernet network as the testbed. The results showed that QoS using CBQ and TBF eliminated packet loss on UDP/IP transfer while the UDP/IP transfer in best effort made lots of packet loss. The result also showed that the QoS overhead was small. The authors concluded that QoS on Linux performed efficiently in TCP/IP and UDP/IP and will have an important role of the Atlas TDAQ system

  3. Soft real-time alarm messages for ATLAS TDAQ

    CERN Document Server

    Darlea, G; Martin, B; Lehmann Miotto, G

    2010-01-01

    The ATLAS TDAQ network consists of three separate Ethernet-based networks (Data, Control and Management) with over 2000 end-nodes. The TDAQ system has to be aware of the meaningful network failures and events in order for it to take effective recovery actions. The first stage of the process is implemented with Spectrum, a commercial network management tool. Spectrum detects and registers all network events, then it publishes the information via a CORBA programming interface. A gateway program (called NSG—Network Service Gateway) connects to Spectrum through CORBA and exposes to its clients a Java RMI interface. This interface implements a callback mechanism that allows the clients to subscribe for monitoring "interesting" parts of the network. The last stage of the TDAQ network monitoring tool is implemented in a module named DNC (DAQ to Network Connection), which filters the events that are to be reported to the TDAQ system: it subscribes to the gateway only for the machines that are currently active in th...

  4. Network Resiliency Implementation in the ATLAS TDAQ System

    CERN Document Server

    Stancu, S N; The ATLAS collaboration

    2010-01-01

    The ATLAS TDAQ system performs the real time selection of events produced by the detector. For this purpose approximately 2000 computers are deployed and interconnected through various high speed networks, whose architecture has already been described. This article focuses on the implementation and validation of network connectivity resiliency (previously presented at a conceptual level). Redundancy and eventually load balancing are achieved through the synergy of various protocols: 802.3ad link aggregation, OSPF, VRRP, MSTP. An innovative method for cost efficient redundant connectivity of high-throughput high-availability servers is presented. Furthermore, real life examples showing how redundancy works, and more importantly how it might fail despite careful planning are presented.

  5. Network Resiliency Implementation in the ATLAS TDAQ System

    CERN Document Server

    Stancu, S N; The ATLAS collaboration; Batraneanu, S M; Ballestrero, S; Caramarcu, C; Martin, B; Savu, D O; Sjoen, R V; Valsan, L

    2010-01-01

    The ATLAS TDAQ (Trigger and Data Acquisition) system performs the real-time selection of events produced by the detector. For this purpose approximately 2000 computers are deployed and interconnected through various high speed networks, whose architecture has already been described. This article focuses on the implementation and validation of network connectivity resiliency (previously presented at a conceptual level). Redundancy and eventually load balancing are achieved through the synergy of various protocols: 802.3ad link aggregation, OSPF (Open Shortest Path First), VRRP (Virtual Router Redundancy Protocol), MST (Multiple Spanning Trees). An innovative method for cost-effective redundant connectivity of high-throughput high-availability servers is presented. Furthermore, real-life examples showing how redundancy works, and more importantly how it might fail despite careful planning are presented.

  6. Soft real-time alarm messages for ATLAS TDAQ

    Science.gov (United States)

    Darlea, G.; Al Shabibi, A.; Martin, B.; Lehmann Miotto, G.

    2010-05-01

    The ATLAS TDAQ network consists of three separate Ethernet-based networks (Data, Control and Management) with over 2000 end-nodes. The TDAQ system has to be aware of the meaningful network failures and events in order for it to take effective recovery actions. The first stage of the process is implemented with Spectrum, a commercial network management tool. Spectrum detects and registers all network events, then it publishes the information via a CORBA programming interface. A gateway program (called NSG—Network Service Gateway) connects to Spectrum through CORBA and exposes to its clients a Java RMI interface. This interface implements a callback mechanism that allows the clients to subscribe for monitoring "interesting" parts of the network. The last stage of the TDAQ network monitoring tool is implemented in a module named DNC (DAQ to Network Connection), which filters the events that are to be reported to the TDAQ system: it subscribes to the gateway only for the machines that are currently active in the system and it forwards only the alarms that are considered important for the current TDAQ data taking session. The network information is then synthesized and presented in a human-readable format. These messages can be further processed either by the shifter who is in charge, the network expert or the Online Expert System. This article aims to describe the different mechanisms of the chain that transports the network events to the front-end user, as well as the constraints and rules that govern the filtering and the final format of the alarm messages.

  7. Soft real-time alarm messages for ATLAS TDAQ

    International Nuclear Information System (INIS)

    Darlea, G.; Al Shabibi, A.; Martin, B.; Lehmann Miotto, G.

    2010-01-01

    The ATLAS TDAQ network consists of three separate Ethernet-based networks (Data, Control and Management) with over 2000 end-nodes. The TDAQ system has to be aware of the meaningful network failures and events in order for it to take effective recovery actions. The first stage of the process is implemented with Spectrum, a commercial network management tool. Spectrum detects and registers all network events, then it publishes the information via a CORBA programming interface. A gateway program (called NSG-Network Service Gateway) connects to Spectrum through CORBA and exposes to its clients a Java RMI interface. This interface implements a callback mechanism that allows the clients to subscribe for monitoring 'interesting' parts of the network. The last stage of the TDAQ network monitoring tool is implemented in a module named DNC (DAQ to Network Connection), which filters the events that are to be reported to the TDAQ system: it subscribes to the gateway only for the machines that are currently active in the system and it forwards only the alarms that are considered important for the current TDAQ data taking session. The network information is then synthesized and presented in a human-readable format. These messages can be further processed either by the shifter who is in charge, the network expert or the Online Expert System. This article aims to describe the different mechanisms of the chain that transports the network events to the front-end user, as well as the constraints and rules that govern the filtering and the final format of the alarm messages.

  8. Soft real-time alarm messages for ATLAS TDAQ

    Energy Technology Data Exchange (ETDEWEB)

    Darlea, G., E-mail: georgiana.lavinia.darlea@cern.c [CERN, Geneva (Switzerland); Al Shabibi, A.; Martin, B.; Lehmann Miotto, G. [CERN, Geneva (Switzerland)

    2010-05-21

    The ATLAS TDAQ network consists of three separate Ethernet-based networks (Data, Control and Management) with over 2000 end-nodes. The TDAQ system has to be aware of the meaningful network failures and events in order for it to take effective recovery actions. The first stage of the process is implemented with Spectrum, a commercial network management tool. Spectrum detects and registers all network events, then it publishes the information via a CORBA programming interface. A gateway program (called NSG-Network Service Gateway) connects to Spectrum through CORBA and exposes to its clients a Java RMI interface. This interface implements a callback mechanism that allows the clients to subscribe for monitoring 'interesting' parts of the network. The last stage of the TDAQ network monitoring tool is implemented in a module named DNC (DAQ to Network Connection), which filters the events that are to be reported to the TDAQ system: it subscribes to the gateway only for the machines that are currently active in the system and it forwards only the alarms that are considered important for the current TDAQ data taking session. The network information is then synthesized and presented in a human-readable format. These messages can be further processed either by the shifter who is in charge, the network expert or the Online Expert System. This article aims to describe the different mechanisms of the chain that transports the network events to the front-end user, as well as the constraints and rules that govern the filtering and the final format of the alarm messages.

  9. ATLAS TDAQ System Administration:

    CERN Document Server

    Lee, Christopher Jon; The ATLAS collaboration; Bogdanchikov, Alexander; Ballestrero, Sergio; Contescu, Alexandru Cristian; Dubrov, Sergei; Fazio, Daniel; Korol, Aleksandr; Scannicchio, Diana; Twomey, Matthew Shaun; Voronkov, Artem

    2015-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) system is responsible for the online processing of live data, streaming from the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The online farm is composed of ̃3000 servers, processing the data readout from ̃100 million detector channels through multiple trigger levels. During the two years of the first Long Shutdown (LS1) there has been a tremendous amount of work done by the ATLAS TDAQ System Administrators, implementing numerous new software applications, upgrading the OS and the hardware, changing some design philosophies and exploiting the High Level Trigger farm with different purposes. During the data taking only critical security updates are applied and broken hardware is replaced to ensure a stable operational environment. The LS1 provided an excellent opportunity to look into new technologies and applications that would help to improve and streamline the daily tasks of not only the System Administrators, but also of the scientists who wil...

  10. Integrated System for Performance Monitoring of ATLAS TDAQ Network

    CERN Document Server

    Savu, D; The ATLAS collaboration; Martin, B; Sjoen, R; Batraneanu, S; Stancu, S

    2010-01-01

    The ATLAS TDAQ Network consists of three separate networks spanning four levels of the experimental building. Over 200 edge switches and 5 multi-blade chassis routers are used to interconnect 2000 processors, adding up to more than 7000 high speed interfaces. In order to substantially speed-up ad-hoc and post mortem analysis, a scalable, yet flexible, integrated system for monitoring both network statistics and environmental conditions, processor parameters and data taking characteristics was required. For successful up-to-the-minute monitoring, information from many SNMP compliant devices, independent databases and custom APIs was gathered, stored and displayed in an optimal way. Easy navigation and compact aggregation of multiple data sources were the main requirements; characteristics not found in any of the tested products, either open-source or commercial. This paper describes how performance, scalability and display issues were addressed and what challenges the project faced during development and deplo...

  11. Report on container technology for the ATLAS TDAQ system

    CERN Document Server

    Gadirov, Hamid

    2016-01-01

    My summer student project "Container technology for the Upgrade of the ATLAS Trigger and Data Acquisition (TDAQ) system" focused on the research of container-based (operating system-level) virtualization for TDAQ software. Several tests were performed on Docker platform, all of them showed compatibility for TDAQ software.

  12. ATLAS TDAQ application gateway upgrade during LS1

    CERN Document Server

    KOROL, A; The ATLAS collaboration; BOGDANCHIKOV, A; BRASOLIN, F; CONTESCU, A C; DUBROV, S; HAFEEZ, M; LEE, C J; SCANNICCHIO, D A; TWOMEY, M; VORONKOV, A; ZAYTSEV, A

    2014-01-01

    The ATLAS Gateway service is implemented with a set of dedicated computer nodes to provide a fine-grained access control between CERN General Public Network (GPN) and ATLAS Technical Control Network (ATCN). ATCN connects the ATLAS online farm used for ATLAS Operations and data taking, including the ATLAS TDAQ (Trigger and Data Aquisition) and DCS (Detector Control System) nodes. In particular, it provides restricted access to the web services (proxy), general login sessions (via SSH and RDP protocols), NAT and mail relay from ATCN. At the Operating System level the implementation is based on virtualization technologies. Here we report on the Gateway upgrade during Long Shutdown 1 (LS1) period: it includes the transition to the last production release of the CERN Linux distribution (SLC6), the migration to the centralized configuration management system (based on Puppet) and the redesign of the internal system architecture.

  13. Analysis and predictive modeling of the performance of the ATLAS TDAQ network

    CERN Document Server

    Leahu, Lucian; Buzuloiu, V; Martin, B

    After almost twenty years of research, development and installation, the Large Hadron Collider (LHC) accelerator at CERN produced its first collisions in 2008, planning to run until the end of 2012. ATLAS (A Torroidal LHC ApparatuS) is the biggest exper- iment built and operated on the LHC ring. Being a general purpose detector, it studies a wide range of physics aspects, out of which the search for the “God particle” - Higgs boson - is its most significant mission. In 2012 ATLAS already recorded collisions data, called events, which were, with a big probability, candidates for proving the ex- istence of this particle. Capturing this type of “interesting” events is the task of the ATLAS detector, however filtering them from the huge amount of data being generated is the purpose of the Trigger and Data Acquisition system (TDAQ). ATLAS TDAQ is implemented as a three layer filter, reducing in real-time the rates of the events (1.6 Mbytes big) down to a level which can be written to mass storage: from 40 ...

  14. The TDAQ Analytics Dashboard: a real-time web application for the ATLAS TDAQ control infrastructure

    CERN Document Server

    Magnoni, L; The ATLAS collaboration; Sloper, J E

    2011-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) infrastructure is responsible for filtering and transferring ATLAS experimental data from detectors to mass storage systems. It relies on a large, distributed computing environment composed by thousands of software applications running concurrently. In such a complex environment, information sharing is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, the streams of messages sent by applications and data published via information services are constantly monitored by experts to verify correctness of running operations and to understand problematic situations. To simplify and improve system analysis and errors detection tasks, we developed the TDAQ Analytics Dashboard, a web application that aims to collect, correlate and visualize effectively this real time flow of information. The TDAQ Analytics Dashboard is composed by two main entities, that reflect the twofold scope of the application. The fi...

  15. The TDAQ Analytics Dashboard: a real-time web application for the ATLAS TDAQ control infrastructure

    CERN Document Server

    Magnoni, L; Sloper, J E

    2010-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) infrastructure is responsible for filtering and transferring ATLAS experimental data from detectors to mass storage systems. It relies on a large, distributed computing environment composed by thousands of software applications running concurrently. In such a complex environment, information sharing is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, the streams of messages sent by applications and data published via information services are constantly monitored by experts to verify correctness of running operations and to understand problematic situations. To simplify and improve system analysis and errors detection tasks, we developed the TDAQ Analytics Dashboard, a web application that aims to collect, correlate and visualize effectively this real time flow of information. The TDAQ Analytics Dashboard is composed by two main entities, that reflect the twofold scope of the application. The fi...

  16. Hybrid Network Simulation for the ATLAS Trigger and Data Acquisition (TDAQ) System

    CERN Document Server

    Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel; Foguelman, Daniel Jacob

    2015-01-01

    The poster shows the ongoing research in the ATLAS TDAQ group in collaboration with the University of Buenos Aires in the area of hybrid data network simulations. he Data Network and Processing Cluster filters data in real-time, achieving a rejection factor in the order of 40000x and has real-time latency constrains. The dataflow between the processing units (TPUs) and Readout System (ROS) presents a “TCP Incast”-type network pathology which TCP cannot handle it efficiently. A credits system is in place which limits rate of queries and reduces latency. This large computer network, and the complex dataflow has been modelled and simulated using a PowerDEVS, a DEVS-based simulator. The simulation has been validated and used to produce what-if scenarios in the real network. Network Simulation with Hybrid Flows: Speedups and accuracy, combined • For intensive network traffic, Discrete Event simulation models (packet-level granularity) soon becomes prohibitive: Too high computing demands. • Fluid Flow simul...

  17. Design and Performance of the Virtualization Platform for Offline computing on the ATLAS TDAQ Farm

    CERN Document Server

    Ballestrero, S; The ATLAS collaboration; Brasolin, F; Contescu, C; Di Girolamo, A; Lee, C J; Pozo Astigarraga, M E; Scannicchio, D A; Twomey, M S; Zaytsev, A

    2013-01-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 (LS1) there is a remarkable opportunity to use the computing resources of the large trigger farms of the experiments for other data processing activities. In the case of ATLAS experiment the TDAQ farm, consisting of more than 1500 compute nodes, is particularly suitable for running Monte Carlo production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of all the stages of Sim@P1 project dedicated to the design and deployment of a virtualized platform running on the ATLAS TDAQ computing resources and using it to run the large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to avoid interference with TDAQ usage of the farm and to guarantee the security and the usability of the ATLAS private network; Openstack has been chosen to provide a cloud management layer. The approaches to organizing support for the sustained operation of...

  18. Design and Performance of the Virtualization Platform for Offline computing on the ATLAS TDAQ Farm

    CERN Document Server

    Ballestrero, S; The ATLAS collaboration; Brasolin, F; Contescu, C; Di Girolamo, A; Lee, C J; Pozo Astigarraga, M E; Scannicchio, D A; Twomey, M S; Zaytsev, A

    2014-01-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 (LS1) there is a remarkable opportunity to use the computing resources of the large trigger farms of the experiments for other data processing activities. In the case of ATLAS experiment the TDAQ farm, consisting of more than 1500 compute nodes, is particularly suitable for running Monte Carlo production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of all the stages of Sim@P1 project dedicated to the design and deployment of a virtualized platform running on the ATLAS TDAQ computing resources and using it to run the large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to avoid interference with TDAQ usage of the farm and to guarantee the security and the usability of the ATLAS private network; Openstack has been chosen to provide a cloud management layer. The approaches to organizing support for the sustained operation of...

  19. IT Infrastructure Design and Implementation Considerations for the ATLAS TDAQ System

    CERN Document Server

    Dobson, M; The ATLAS collaboration; Caramarcu, C; Dumitru, I; Valsan, L; Darlea, G L; Bujor, F; Bogdanchikov, A G; Korol, A A; Zaytsev, A S; Ballestrero, S

    2013-01-01

    This paper gives a thorough overview of the ATLAS TDAQ SysAdmin group activities which deals with administration of the TDAQ computing environment supporting Front End detector hardware, Data Flow, Event Filter and other subsystems of the ATLAS detector operating on the LHC accelerator at CERN. The current installation consists of approximately 1500 netbooted nodes managed by more than 60 dedicated servers, a high performance centralized storage system, about 50 multi-screen user interface systems installed in the control rooms and various hardware and critical service monitoring machines. In the final configuration, the online computer farm will be capable of hosting tens of thousands applications running simultaneously. The ATLAS TDAQ computing environment is now serving more than 3000 users subdivided into approximately 300 categories in correspondence with their roles in the system. The access and role management system is custom built on top of an LDAP schema. The engineering infrastructure of the ATLAS ...

  20. Error Management in ATLAS TDAQ: An Intelligent Systems approach

    CERN Document Server

    Slopper, John Erik

    2010-01-01

    This thesis is concerned with the use of intelligent system techniques (IST) within a large distributed software system, specically the ATLAS TDAQ system which has been developed and is currently in use at the European Laboratory for Particle Physics(CERN). The overall aim is to investigate and evaluate a range of ITS techniques in order to improve the error management system (EMS) currently used within the TDAQ system via error detection and classication. The thesis work will provide a reference for future research and development of such methods in the TDAQ system. The thesis begins by describing the TDAQ system and the existing EMS, with a focus on the underlying expert system approach, in order to identify areas where improvements can be made using IST techniques. It then discusses measures of evaluating error detection and classication techniques and the factors specic to the TDAQ system. Error conditions are then simulated in a controlled manner using an experimental setup and datasets were gathered fro...

  1. ATLAS TDAQ System Administration: an overview and evolution

    CERN Document Server

    LEE, CJ; The ATLAS collaboration; BOGDANCHIKOV, A; BRASOLIN, F; CONTESCU, AC; DARLEA, G-L; KOROL, A; SCANNICCHIO, DA; TWOMEY, M; VALSAN, ML

    2013-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) system is responsible for the online processing of live data streaming from the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The system processes the direct data readout from ~100 million channels on the detector through multiple trigger levels, selecting interesting events for analysis with a factor of $10^{7}$ reduction on the data rate with a latency of less than a few seconds. Most of the functionality is implemented on ~3000 servers composing the online farm. Due to the critical functionality of the system a sophisticated computing environment is maintained, covering the online farm and ATLAS control rooms, as well as a number of development and testing labs. The specificity of the system required the development of dedicated applications (e.g. ConfDB, BWM) for system configuration and maintenance; in parallel other Open Source tools (Puppet and Quattor) are used to centrally configure the operating systems. The health monitoring of the TDAQ s...

  2. ATLAS TDAQ System Administration: an overview and evolution

    CERN Document Server

    LEE, CJ; The ATLAS collaboration; BOGDANCHIKOV, A; BRASOLIN, F; CONTESCU, AC; DARLEA, GL; KOROL, A; SCANNICCHIO, DA; TWOMEY, M; VALSAN, ML

    2013-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) system is responsible for the online processing of live data streaming from the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The system processes the direct data readout from ~100 million channels on the detector through three trigger levels, selecting interesting events for analysis with a factor of 10^7 reduction on the data rate with a latency of less than a few seconds. Most of the functionality is implemented on ~3000 servers composing the online farm. Due to the critical functionality of the system a sophisticated computing environment is maintained, covering the online farm and ATLAS control rooms, as well as a number of development and testing labs. The specificity of the system required the development of dedicated applications (e.g. ConfDB, BWM) for system configuration and maintenance; in parallel other Open Source tools (Puppet and Quattor) are used to centrally configure the operating systems. The health monitoring of the TDAQ system h...

  3. ATLAS TDAQ System Administration: evolution and re-design

    CERN Document Server

    Ballestrero, Sergio; The ATLAS collaboration; Brasolin, Franco; Contescu, Alexandru Cristian; Dubrov, Sergei; Fazio, Daniel; Korol, Aleksandr; Lee, Christopher Jon; Scannicchio, Diana; Twomey, Matthew Shaun

    2015-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) system is responsible for the online processing of live data, streaming from the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. The online farm is composed of $\\sim 3000$ servers, processing the data readout from $\\sim 100$ million detector channels through multiple trigger levels. During the two years of the first Long Shutdown (LS1) there has been a tremendous amount of work done by the ATLAS TDAQ System Administrators, implementing numerous new software applications, upgrading the OS and the hardware, changing some design philosophies and exploiting the High Level Trigger farm with different purposes. The OS version has been upgraded to SLC6; for the largest part of the farm, which is composed by net booted nodes, this required a completely new design of the net booting system. In parallel, the migration to Puppet of the Configuration Management systems has been completed for both net booted and local booted hosts; the Post-Boot Scripts system and...

  4. Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

    Science.gov (United States)

    Ballestrero, S.; Batraneanu, S. M.; Brasolin, F.; Contescu, C.; Di Girolamo, A.; Lee, C. J.; Pozo Astigarraga, M. E.; Scannicchio, D. A.; Twomey, M. S.; Zaytsev, A.

    2014-06-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

  5. The TDAQ Analytics Dashboard: a real-time web application for the ATLAS TDAQ control infrastructure

    International Nuclear Information System (INIS)

    Miotto, Giovanna Lehmann; Magnoni, Luca; Sloper, John Erik

    2011-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) infrastructure is responsible for filtering and transferring ATLAS experimental data from detectors to mass storage systems. It relies on a large, distributed computing system composed of thousands of software applications running concurrently. In such a complex environment, information sharing is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking, the streams of messages sent by applications and data published via information services are constantly monitored by experts to verify the correctness of running operations and to understand problematic situations. To simplify and improve system analysis and errors detection tasks, we developed the TDAQ Analytics Dashboard, a web application that aims to collect, correlate and visualize effectively this real time flow of information. The TDAQ Analytics Dashboard is composed of two main entities that reflect the twofold scope of the application. The first is the engine, a Java service that performs aggregation, processing and filtering of real time data stream and computes statistical correlation on sliding windows of time. The results are made available to clients via a simple web interface supporting SQL-like query syntax. The second is the visualization, provided by an Ajax-based web application that runs on client's browser. The dashboard approach allows to present information in a clear and customizable structure. Several types of interactive graphs are proposed as widgets that can be dynamically added and removed from visualization panels. Each widget acts as a client for the engine, querying the web interface to retrieve data with desired criteria. In this paper we present the design, development and evolution of the TDAQ Analytics Dashboard. We also present the statistical analysis computed by the application in this first period of high energy data taking operations for the ATLAS experiment.

  6. Advanced Visualization System for Monitoring the ATLAS TDAQ Network in real-time

    CERN Document Server

    Batraneanu, S M; The ATLAS collaboration; Martin, B; Savu, D O; Stancu, S N; Leahu, L

    2012-01-01

    The trigger and data acquisition (TDAQ) system of the ATLAS experiment at CERN comprises approximately 2500 servers interconnected by three separate Ethernet networks, totaling 250 switches. Due to its real-time nature, there are additional requirements in comparison to conventional networks in terms of speed and performance. A comprehensive monitoring framework has been developed for expert use. However, non experts may experience difficulties in using it and interpreting data. Moreover, specific performance issues, such as single component saturation or unbalanced workload, need to be spotted with ease, in real-time, and understood in the context of the full system view. We addressed these issues by developing an innovative visualization system where the users benefit from the advantages of 3D graphics to visualize the large monitoring parameter space associated with our system. This has been done by developing a hierarchical model of the complete system onto which we overlaid geographical, logical and real...

  7. Intelligent monitoring and fault diagnosis for ATLAS TDAQ: a complex event processing solution

    CERN Document Server

    Magnoni, Luca; Luppi, Eleonora

    Effective monitoring and analysis tools are fundamental in modern IT infrastructures to get insights on the overall system behavior and to deal promptly and effectively with failures. In recent years, Complex Event Processing (CEP) technologies have emerged as effective solutions for information processing from the most disparate fields: from wireless sensor networks to financial analysis. This thesis proposes an innovative approach to monitor and operate complex and distributed computing systems, in particular referring to the ATLAS Trigger and Data Acquisition (TDAQ) system currently in use at the European Organization for Nuclear Research (CERN). The result of this research, the AAL project, is currently used to provide ATLAS data acquisition operators with automated error detection and intelligent system analysis. The thesis begins by describing the TDAQ system and the controlling architecture, with a focus on the monitoring infrastructure and the expert system used for error detection and automated reco...

  8. Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

    International Nuclear Information System (INIS)

    Ballestrero, S; Lee, C J; Batraneanu, S M; Scannicchio, D A; Brasolin, F; Contescu, C; Girolamo, A Di; Astigarraga, M E Pozo; Twomey, M S; Zaytsev, A

    2014-01-01

    With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

  9. ATLAS TDAQ system administration: Master of Puppets

    CERN Document Server

    AUTHOR|(SzGeCERN)727357; The ATLAS collaboration; Ballestrero, Sergio; Brasolin, Franco; Fazio, Daniel; Gament, Costin-Eugen; Scannicchio, Diana; Twomey, Matthew Shaun

    2017-01-01

    Within the ATLAS detector, the Trigger and Data Acquisition system is responsible for the online processing of data streamed from the detector during collisions at the Large Hadron Collider at CERN. The online farm is comprised of ∼4000 servers processing the data read out from ∼100 million detector channels through multiple trigger levels. The configurtion of these servers is not an easy task, especially since the detector itself is made up of multiple different sub-detectors, each with their own particular requirements. The previous method of configuring these servers, using Quattor and a hierarchical scripts system was cumbersome and restrictive. A better, unified system was therefore required to simplify the tasks of the TDAQ Systems Administrators, for both the local and net-booted systems, and to be able to fulfil the requirements of TDAQ, Detector Control Systems and the sub-detectors groups. Various configuration management systems were evaluated, though in the end, Puppet was chosen as the applic...

  10. Technical Design Report for the Phase-I Upgrade of the ATLAS TDAQ System

    CERN Document Server

    AUTHOR|(CDS)2069742; Abbott, Brad; Abdallah, Jalal; Abdel Khalek, Samah; Abdinov, Ovsat; Aben, Rosemarie; Abi, Babak; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Achenbach, Ralf; Adamczyk, Leszek; Adams, David; Adelman, Jahred; Adomeit, Stefanie; Adye, Tim; Aefsky, Scott; Agatonovic-Jovin, Tatjana; Aguilar-Saavedra, Juan Antonio; Agustoni, Marco; Ahlen, Steven; Ahmad, Ashfaq; Ahmadov, Faig; Aielli, Giulio; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Alam, Muhammad Aftab; Albert, Justin; Albrand, Solveig; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexandrov, Evgeny; Alexopoulos, Theodoros; Alhroob, Muhammad; Alimonti, Gianluca; Alio, Lion; Alison, John; Allbrooke, Benedict; Allison, Lee John; Allport, Phillip; Allwood-Spiers, Sarah; Almond, John; Aloisio, Alberto; Alon, Raz; Alonso, Alejandro; Alonso, Francisco; Altheimer, Andrew David; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amaral Coutinho, Yara; Amelung, Christoph; Amor Dos Santos, Susana Patricia; Amoroso, Simone; Amram, Nir; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, John Thomas; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Anduaga, Xabier; Angelidakis, Stylianos; Angelozzi, Ivan; Anger, Philipp; Angerami, Aaron; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Araujo Ferraz, Victor; Arce, Ayana; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnal, Vanessa; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Asai, Shoji; Asbah, Nedaa; Ask, Stefan; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Auerbach, Benjamin; Augsten, Kamil; Augusto, José; Aurousseau, Mathieu; Avolio, Giuseppe; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baas, Alessandra; Bach, Andre; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Backus Mayes, John; Badescu, Elisabeta; Bagiacchi, Paolo; Bagnaia, Paolo; Bai, Yu; Bain, Travis; Baines, John; Baker, Oliver Keith; Baker, Sarah; Balek, Petr; Ballestrero, Sergio; Balli, Fabrice; Banas, Elzbieta; Banerjee, Swagato; Bangert, Andrea Michelle; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Barber, Tom; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Bartsch, Valeria; Bassalat, Ahmed; Basye, Austin; Bates, Richard; Batkova, Lucia; Batley, Richard; Batraneanu, Silvia; Battistin, Michele; Bauer, Florian; Bauss, Bruno; Bawa, Harinder Singh; Beacham, James Baker; Beau, Tristan; Beauchemin, Pierre-Hugues; Bechtle, Philip; Beck, Hans Peter; Becker, Anne Kathrin; Becker, Sebastian; Beckingham, Matthew; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Beemster, Lars; Beermann, Thomas; Begel, Michael; Behr, Katharina; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belloni, Alberto; Belotskiy, Konstantin; Beltramello, Olga; Benary, Odette; Benchekroun, Driss; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Bensinger, James; Bentvelsen, Stan; Beretta, Matteo; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Berglund, Elina; Beringer, Jürg; Bernard, Clare; Bernat, Pauline; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertelsen, Henrik; Bertolucci, Federico; Besana, Maria Ilaria; Besjes, Geert-Jan; Bessidskaia Bylund, Olga; Besson, Nathalie; Betancourt, Christopher; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianchini, Louis; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilbao De Mendizabal, Javier; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Bittner, Bernhard; Black, Curtis; Black, James; Black, Kevin; Blackburn, Daniel; Blair, Robert; Blanchard, Jean-Baptiste; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Boddy, Christopher Richard; Boehler, Michael; Boek, Jennifer; Boek, Thorsten Tobias; Bogdan, Mircea Arghir; Bogdanchikov, Alexander; Bohm, Christian; Boisvert, Veronique; Bold, Tomasz; Boldyrev, Alexey; Bolnet, Nayanka Myriam; 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Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Budick, Burton; Buehrer, Felix; Bugge, Lars; Bugge, Magnar Kopangen; Bulekov, Oleg; Bundock, Aaron Colin; Bunse, Moritz; Burdin, Sergey; Burghgrave, Blake; Burke, Stephen; Burmeister, Ingo; Busato, Emmanuel; Büscher, Volker; Bussey, Peter; Buszello, Claus-Peter; Butler, Bart; Butler, John; Butt, Aatif Imtiaz; Buttar, Craig; Butterworth, Jonathan; Buttinger, William; Buzatu, Adrian; Byszewski, Marcin; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Cameron, David; Caminada, Lea Michaela; Caminal Armadans, Roger; Campana, Simone; Campanelli, Mario; Campoverde, Angel; Canale, Vincenzo; Canelli, Florencia; Canepa, Anadi; Cantero, Josu; Cantrill, Robert; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capua, Marcella; Caputo, Regina; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Sascha; Carquin, Edson; Carrillo-Montoya, German D; Carter, Janet; Casadei, Diego; Casado, Maria Pilar; Castaneda-Miranda, Elizabeth; Castelli, Angelantonio; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Catastini, Pierluigi; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cavaliere, Viviana; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerio, Benjamin; Cerny, Karel; Cerqueira, Augusto Santiago; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cerv, Matevz; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chalupkova, Ina; Chan, Kevin; Chang, Philip; Chapleau, Bertrand; Chapman, John Derek; Charfeddine, Driss; Charlton, Dave; Chavda, Vikash; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Karen; Chen, Liming; Chen, Shenjian; Chen, Xin; Chen, Yujiao; Cheng, Hok Chuen; Cheng, Yangyang; Cheplakov, Alexander; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Chevalier, Laurent; Chiarella, Vitaliano; Chiefari, Giovanni; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chislett, Rebecca Thalatta; Chitan, Adrian; Chizhov, Mihail; Chouridou, Sofia; Chow, Bonnie Kar Bo; Christidi, Ilektra-Athanasia; Chudoba, Jiri; Ciapetti, Guido; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciocio, Alessandra; Ciodaro Xavier, Thiago; Cirkovic, Predrag; Citraro, Saverio; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Clarke, Robert; Clemens, Jean-Claude; Clement, Benoit; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coffey, Laurel; Cogan, Joshua Godfrey; Coggeshall, James; Cole, Brian; Cole, Stephen; Colijn, Auke-Pieter; Collins-Tooth, Christopher; Collot, Johann; Colombo, Tommaso; Colon, German; Compostella, Gabriele; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Connelly, Ian; Consonni, Sofia Maria; Consorti, Valerio; Constantinescu, Serban; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cooper-Smith, Neil; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Corso-Radu, Alina; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Côté, David; Cottin, Giovanna; Coura Torres, Rodrigo; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Cree, Graham; Crépé-Renaudin, Sabine; Crescioli, Francesco; Crispin Ortuzar, Mireia; Cristinziani, Markus; Crone, Gordon Jeremy; Crosetti, Giovanni; Cuciuc, Constantin-Mihai; Cuenca Almenar, Cristóbal; Cuhadar Donszelmann, Tulay; Cummings, Jane; Curatolo, Maria; Cuthbert, Cameron; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; D'Orazio, Alessia; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dafinca, Alexandru; Dai, Tiesheng; Dale, Orjan; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Daniells, Andrew Christopher; Dano Hoffmann, Maria; Dao, Valerio; Darbo, Giovanni; Darlea, Georgiana Lavinia; Darmora, Smita; Dassoulas, James; Davey, Will; David, Claire; Davidek, Tomas; Davies, Eleanor; Davies, Merlin; Davignon, Olivier; Davison, Adam; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Daya-Ishmukhametova, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Cecco, Sandro; de Graat, Julien; De Groot, Nicolo; de Jong, Paul; De la Torre, Hector; De Lorenzi, Francesco; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dechenaux, Benjamin; Dedovich, Dmitri; Degenhardt, James; Deigaard, Ingrid; Del Peso, Jose; Del Prete, Tarcisio; Delemontex, Thomas; Deliot, Frederic; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Dell'Orso, Mauro; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deviveiros, Pier-Olivier; Dewhurst, Alastair; Dhaliwal, Saminder; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Domenico, Antonio; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Di Valentino, David; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dimitrievska, Aleksandra; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; do Vale, Maria Aline Barros; Doan, Thi Kieu Oanh; Dobos, Daniel; Dobson, Ellie; Doglioni, Caterina; Doherty, Tom; Dohmae, Takeshi; Dolejsi, Jiri; Dolezal, Zdenek; Donadelli, Marisilvia; Donati, Simone; Dondero, Paolo; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dova, Maria-Teresa; Doyle, Tony; Drake, Gary; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Dubreuil, Emmanuelle; Duchovni, Ehud; Duckeck, Guenter; Ducu, Otilia Anamaria; Duda, Dominik; Dudarev, Alexey; Dudziak, Fanny; Duflot, Laurent; Duguid, Liam; Dührssen, Michael; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Dwuznik, Michal; Ebke, Johannes; Edmunds, Daniel; Edson, William; Edwards, Clive; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Endo, Masaki; Erdmann, Johannes; Ereditato, Antonio; Ermoline, Iouri; Ernis, Gunar; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Esch, Hendrik; Escobar, Carlos; Esposito, Bellisario; Etienvre, Anne-Isabelle; Etzion, Erez; Evangelakou, Despoina; Evans, Hal; Fabbri, Laura; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Faltova, Jana; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Fatholahzadeh, Baharak; Faulkner, Peter; Favareto, Andrea; Fayard, Louis; Federic, Pavol; Fedin, Oleg; Fedorko, Wojciech; Fehling-Kaschek, Mirjam; Feigl, Simon; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenyuk, Alexander; Fernandez Perez, Sonia; Ferrag, Samir; Ferrando, James; Ferrara, Valentina; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipčič, Andrej; Filipuzzi, Marco; Filthaut, Frank; Fincke-Keeler, Margret; Finelli, Kevin Daniel; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Julia; Fisher, Matthew; Fitzgerald, Eric Andrew; Flechl, Martin; Fleck, Ivor; Fleischmann, Philipp; Fleischmann, Sebastian; Fletcher, Gareth Thomas; Fletcher, Gregory; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Florez Bustos, Andres Carlos; Flowerdew, Michael; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Fournier, Daniel; Fox, Harald; Francavilla, Paolo; Franchini, Matteo; Franchino, Silvia; Francis, David; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; Fratina, Sasa; French, Sky; Friedrich, Conrad; Friedrich, Felix; Froidevaux, Daniel; Front, David Moris; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fulsom, Bryan Gregory; Fusayasu, Takahiro; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gadatsch, Stefan; Gadfort, Thomas; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Galster, Gorm Aske Gram Krohn; Gan, KK; Gandrajula, Reddy Pratap; Gao, Jun; Gao, Yongsheng; Garay Walls, Francisca; Garberson, Ford; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Ge, Peng; Gecse, Zoltan; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; Gentsos, Christos; George, Matthias; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghibaudi, Marco; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giangiobbe, Vincent; Giannetti, Paola; Gianotti, Fabiola; Gibson, Stephen; Gillam, Thomas; Gillberg, Dag; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Francesco Michelangelo; Giovannini, Paola; Giraud, Pierre-Francois; Giugni, Danilo; Giuliani, Claudia; Giulini, Maddalena; Giunta, Michele; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glazov, Alexandre; Glonti, George; Goblirsch-Kolb, Maximilian; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goeringer, Christian; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Gama, Rafael; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez Silva, Laura; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabas, Herve Marie Xavier; Graber, Lars; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Gray, Heather; Gray, Julia Ann; Graziani, Enrico; Grebenyuk, Oleg; Green, Barry; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grohs, Johannes Philipp; Grohsjean, Alexander; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Groth-Jensen, Jacob; Grout, Zara Jane; Grybel, Kai; Guan, Liang; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guicheney, Christophe; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Gunther, Jaroslav; Guo, Jun; Gupta, Shaun; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guttman, Nir; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haas, Stefan; Haber, Carl; Hadavand, Haleh Khani; Haefner, Petra; Hageböck, Stephan; Hakobyan, Hrachya; Haleem, Mahsana; Hall, David; Halladjian, Garabed; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Hanke, Paul; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hansson, Per; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Paul Fraser; Hartjes, Fred; Hasegawa, Satoshi; Hasegawa, Yoji; Hassani, Samira; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hayashi, Takayasu; Hayden, Daniel; Hays, Chris; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Lukas; Heisterkamp, Simon; Hejbal, Jiri; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, James; Henderson, Robert; Hengler, Christopher; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Hensel, Carsten; Herbert, Geoffrey Henry; Hernández Jiménez, Yesenia; Herrberg-Schubert, Ruth; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hickling, Robert; Higón-Rodriguez, Emilio; Higuchi, Kota; Hill, John; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hofmann, Julia Isabell; Hohlfeld, Marc; Holmes, Tova Ray; Hong, Tae Min; Hooft van Huysduynen, Loek; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howard, Jacob; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Xueye; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huettmann, Antje; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Hülsing, Tobias Alexander; Hurwitz, Martina; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Ideal, Emma; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikematsu, Katsumasa; Ikeno, Masahiro; Ilchenko, Iurii; Iliadis, Dimitrios; Ilic, Nikolina; Inamaru, Yuki; Ince, Tayfun; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Iturbe Ponce, Julia Mariana; Ivashin, Anton; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, John; Jackson, Matthew; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobi, Katharina Bianca; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jakubek, Jan; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansen, Hendrik; Janssen, Jens; Jansweijer, Peter Paul Maarten; Janus, Michel; Jarlskog, Göran; Jeanty, Laura; Jeng, Geng-yuan; Jennens, David; Jenni, Peter; Jentzsch, Jennifer; Jeske, Carl; Jézéquel, Stéphane; Jha, Manoj Kumar; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Joergensen, Morten Dam; Johansson, Erik; Johansson, Per; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tim; Joos, Markus; Jorge, Pedro; Joshi, Kiran Daniel; Jovicevic, Jelena; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Jussel, Patrick; Juste Rozas, Aurelio; Kaci, Mohammed; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kahra, Christian; Kajomovitz, Enrique; Kaluza, Adam; Kama, Sami; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kanno, Takayuki; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karastathis, Nikolaos; Karnevskiy, Mikhail; Karpov, Sergey; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Katre, Akshay; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazama, Shingo; Kazanin, Vassili; Kazarinov, Makhail; Kazarov, Andrei; Keeler, Richard; Kehoe, Robert; Keil, Markus; Keller, John; Kempster, Jacob Julian; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Keyes, Robert; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Kharchenko, Dmitri; Khodinov, Alexander; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kiese, Patric Karl; Kim, Hyeon Jin; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kitamura, Takumi; Kiuchi, Kenji; Kladiva, Eduard; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klimkovich, Tatsiana; Klingenberg, Reiner; Klinger, Joel Alexander; Klioutchnikova, Tatiana; Klok, Peter; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohlmann, Simon; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kolanoski, Hermann; Koletsou, Iro; Koll, James; Kolos, Serguei; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Köneke, Karsten; König, Adriaan; K{ö}nig, Sebastian; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitriy; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, Jana; Kravchenko, Anton; Kreiss, Sven; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Nina; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruse, Amanda; Kruse, Mark; Kruskal, Michael; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Andrew; Kuhl, Thorsten; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunigo, Takuto; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurochkin, Yurii; Kurumida, Rie; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; La Rosa, Alessandro; La Rotonda, Laura; Lablak, Said; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laier, Heiko; Laisne, Emmanuel; Lambourne, Luke; Lampen, Caleb; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lang, Valerie Susanne; Lange, Clemens; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Lanza, Agostino; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Larner, Aimee; Lassnig, Mario; Laurelli, Paolo; Laurens, Philippe; Lavorini, Vincenzo; Lavrijsen, Wim; Laycock, Paul; Le, Bao Tran; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Menedeu, Eve; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Claire, Alexandra; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzi, Bruno; Leone, Robert; Leonhardt, Kathrin; Leonidopoulos, Christos; Leontsinis, Stefanos; Leroy, Claude; Lester, Christopher; Lester, Christopher Michael; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Bo; Li, Haifeng; Li, Ho Ling; Li, Shu; Li, Xuefei; Liang, Zhijun; Liao, Hongbo; Liberali, Valentino; Liberti, Barbara; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limbach, Christian; Limosani, Antonio; Lin, Simon; Linde, Frank; Lindquist, Brian Edward; Linnemann, James; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Dong; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Lombardo, Vincenzo Paolo; Long, Brian Alexander; Long, Jonathan; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lopez Paredes, Brais; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Luciano, Pierluigi; Lucotte, Arnaud; Ludwig, Dörthe; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Johan; Lundberg, Olof; Lund-Jensen, Bengt; Lungwitz, Matthias; Luongo, Carmela; Lupu, Nachman; Lynn, David; Lysak, Roman; Lytken, Else; Ma, Hong; Ma, Lian Liang; Maccarrone, Giovanni; Macchiolo, Anna; Maček, Boštjan; Macey, Tom; Machado Miguens, Joana; Macina, Daniela; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeno, Mayuko; Maeno, Tadashi; Magnoni, Luca; Magradze, Erekle; Mahboubi, Kambiz; Mahlstedt, Joern; Mahmoud, Sara; Maiani, Camilla; Maidantchik, Carmen; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Maldaner, Stephan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mamuzic, Judita; Mandelli, Beatrice; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Manfredini, Alessandro; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany Andreina; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Mantifel, Rodger; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchese, Fabrizio; Marchiori, Giovanni; Marcisovsky, Michal; Marino, Christopher; Marroquim, Fernando; Marshall, Zach; Marti, Lukas Fritz; Marti-Garcia, Salvador; Martin, Brian; Martin, Brian; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Homero; Martinez, Mario; Martin-Haugh, Stewart; Martyniuk, Alex; Marx, Marilyn; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massa, Lorenzo; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Matsunaga, Hiroyuki; Matsushita, Takashi; Mättig, Peter; Mättig, Stefan; Mattmann, Johannes; Mattravers, Carly; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazzaferro, Luca; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; Mcfayden, Josh; Mchedlidze, Gvantsa; Mclaughlan, Tom; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Medinnis, Michael; Meehan, Samuel; Meera-Lebbai, Razzak; Meessen, Christophe; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Meloni, Federico; Mendoza Navas, Luis; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mercurio, Kevin Michael; Mergelmeyer, Sebastian; Meric, Nicolas; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Meyer, Joerg; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Miñano Moya, Mercedes; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Mitsui, Shingo; Miucci, Antonio; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Moeller, Victoria; Mohapatra, Soumya; Molander, Simon; Moles-Valls, Regina; Mönig, Klaus; Monini, Caterina; Monk, James; Monnier, Emmanuel; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Mora Herrera, Clemencia; Moraes, Arthur; Morange, Nicolas; Morel, Julien; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Mount, Richard; Mountricha, Eleni; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Klemens; Mueller, Thibaut; Mueller, Timo; Muenstermann, Daniel; Munwes, Yonathan; Murillo Garcia, Raul; Murillo Quijada, Javier Alberto; Murray, Bill; Mussche, Ido; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nackenhorst, Olaf; Nadal, Jordi; Nagai, Koichi; Nagai, Ryo; Nagai, Yoshikazu; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Nanava, Gizo; Napier, Austin; Narayan, Rohin; Nash, Michael; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Negri, Andrea; Negri, Guido; Negrini, Matteo; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neusiedl, Andrea; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen, Duong Hai; Nguyen Thi Hong, Van; Nickerson, Richard; Nicolaidou, Rosy; Nielsen, Jason; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolaidis, Spyridon; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Norberg, Scarlet; Nordberg, Markus; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nuncio-Quiroz, Adriana-Elizabeth; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; Nuti, Francesco; O'Brien, Brendan Joseph; O'grady, Fionnbarr; O'Neil, Dugan; O'Shea, Val; Oakes, Louise Beth; Oakham, Gerald; Oberlack, Horst; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohshima, Takayoshi; Ohshita, Hidetoshi; Okamura, Wataru; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olivito, Dominick; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onyisi, Peter; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Owen, Simon; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagan Griso, Simone; Paganis, Efstathios; Pahl, Christoph; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Palestini, Sandro; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panduro Vazquez, William; Panes, Boris; Pani, Priscilla; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Parker, Michael Andrew; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pasqualucci, Enrico; Passaggio, Stefano; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pearce, James; Pedersen, Maiken; Pedraza Lopez, Sebastian; Pedro, Rute; Peleganchuk, Sergey; Pelikan, Daniel; Peng, Haiping; Penning, Bjoern; Penwell, John; Perepelitsa, Dennis; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perini, Laura; Pernegger, Heinz; Perrella, Sabrina; Peschke, Richard; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Petteni, Michele; Pezoa, Raquel; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Piccinini, Maurizio; Piec, Sebastian Marcin; Piegaia, Ricardo; Piendibene, Marco; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Pingel, Almut; Pinto, Belmiro; Pizio, Caterina; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Plucinski, Pawel; Poddar, Sahill; Podlyski, Fabrice; Poettgen, Ruth; Poggioli, Luc; Pohl, David-leon; Pohl, Martin; Polesello, Giacomo; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Pollard, Christopher Samuel; Polychronakos, Venetios; Pomeroy, Daniel; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Portell Bueso, Xavier; Pospisil, Stanislav; Potamianos, Karolos; Potrap, Igor; Potter, Christina; Potter, Christopher; Poveda, Joaquin; Pozdnyakov, Valery; Pozo Astigarraga, Mikel Eukeni; Prabhu, Robindra; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Price, Darren; Price, Joe; Price, Lawrence; Primavera, Margherita; Proissl, Manuel; Prokofiev, Kirill; Prokoshin, Fedor; Protopapadaki, Eftychia-sofia; Protopopescu, Serban; Proudfoot, James; Prudent, Xavier; Przybycien, Mariusz; Przysiezniak, Helenka; Psoroulas, Serena; Ptacek, Elizabeth; Pueschel, Elisa; Puldon, David; Purohit, Milind; Puzo, Patrick; Pylypchenko, Yuriy; Qian, Jianming; Qian, Weiming; Quadt, Arnulf; Quarrie, David; Quayle, William; Quilty, Donnchadha; Quinonez, Fernando; Radescu, Voica; Radhakrishnan, Sooraj Krishnan; Radloff, Peter; Ragusa, Francesco; Rahal, Ghita; Rajagopalan, Srinivasan; Rammensee, Michael; Rammes, Marcus; Randle-Conde, Aidan Sean; Rangel-Smith, Camila; Rao, Kanury; Rauscher, Felix; Rave, Stefan; Rave, Tobias Christian; Ravenscroft, Thomas; Raymond, Michel; Read, Alexander Lincoln; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Rehnisch, Laura; Reinsch, Andreas; Reisin, Hernan; Reiss, Andreas; Relich, Matthew; Rembser, Christoph; Renaud, Adrien; Rescigno, Marco; Resconi, Silvia; Rezanova, Olga; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Ridel, Melissa; Rieck, Patrick; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Ritsch, Elmar; Riu, Imma; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Rocha de Lima, Jose Guilherme; Roda, Chiara; Roda Dos Santos, Denis; Rodrigues, Luis; Roe, Shaun; Røhne, Ole; Romaniouk, Anatoli; Romano, Marino; Romeo, Gaston; Romero Adam, Elena; Romero Maltrana, Diego; Rompotis, Nikolaos; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Anthony; Rose, Matthew; Rosendahl, Peter Lundgaard; Rosenthal, Oliver; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rosten, Rachel; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexandre; Rozen, Yoram; Ruan, Xifeng; Rubbo, Francesco; Rubinskiy, Igor; Rud, Viacheslav; Rudolph, Christian; Rudolph, Matthew Scott; Rühr, Frederik; Ruiz-Martinez, Aranzazu; Rurikova, Zuzana; Rusakovich, Nikolai; Ruschke, Alexander; Rutherfoord, John; Ruthmann, Nils; Ruzicka, Pavel; Ryabov, Yury; Rybar, Martin; Rybkin, Grigori; Ryder, Nick; Saavedra, Aldo; Sacerdoti, Sabrina; Saddique, Asif; Sadeh, Iftach; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Sakamoto, Hiroshi; Sakurai, Yuki; Salamanna, Giuseppe; Salamon, Andrea; Saleem, Muhammad; Salek, David; Sales De Bruin, Pedro Henrique; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Sanchez, Arturo; Sánchez, Javier; Sanchez Martinez, Victoria; Sandaker, Heidi; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sankey, Dave; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapp, Kevin; Sapronov, Andrey; Saraiva, João; Sarkisyan-Grinbaum, Edward; Sarrazin, Bjorn; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Yuichi; Sauvan, Emmanuel; Sauvan, Jean-Baptiste; Savage, Graham; Savard, Pierre; Savu, Dan Octavian; Sawyer, Craig; Sawyer, Lee; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scanlon, Tim; Scannicchio, Diana; Scarcella, Mark; Schaarschmidt, Jana; Schacht, Peter; Schaefer, Douglas; Schaeffer, Jan; Schaelicke, Andreas; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R~Dean; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schettino, Vinicius; Schiavi, Carlo; Schieck, Jochen; Schillo, Christian; Schioppa, Marco; Schlenker, Stefan; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Christopher; Schmitt, Klaus; Schmitt, Sebastian; Schneider, Basil; Schnellbach, Yan Jie; Schnoor, Ulrike; Schoeffel, Laurent; Schoening, Andre; Schoenrock, Bradley Daniel; Schorlemmer, Andre Lukas; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schramm, Steven; Schreyer, Manuel; Schroeder, Christian; Schroer, Nicolai; Schuh, Natascha; Schultens, Martin Johannes; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwartzman, Ariel; Schwegler, Philipp; Schwemling, Philippe; Schwienhorst, Reinhard; Schwindling, Jerome; Schwindt, Thomas; Schwoerer, Maud; Sciacca, Gianfranco; Scifo, Estelle; Sciolla, Gabriella; Scott, Bill; Scuri, Fabrizio; Scutti, Federico; Searcy, Jacob; Sedov, George; Sedykh, Evgeny; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Sekula, Stephen; Selbach, Karoline Elfriede; Seliverstov, Dmitry; Sellers, Graham; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Serre, Thomas; Seuster, Rolf; Severini, Horst; Sforza, Federico; Sfyrla, Anna; Shabalina, Elizaveta; Shamim, Mansoora; Shan, Lianyou; Shank, James; Shao, Qi Tao; Shapiro, Marjorie; Shatalov, Pavel; Shaw, Kate; Shehu, Ciwake Yusufu; Sherwood, Peter; Shimizu, Shima; Shimmin, Chase Owen; Shimojima, Makoto; Shiyakova, Mariya; Shmeleva, Alevtina; Shochet, Mel; Shooltz, Dean; Short, Daniel; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Shushkevich, Stanislav; Sicho, Petr; Sicoe, Alexandru Dan; Sidiropoulou, Ourania; Sidorov, Dmitri; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silbert, Ohad; Silva, José; Silva Oliveira, Marcos Vinicius; Silver, Yiftah; Silverstein, Daniel; Silverstein, Samuel; Simak, Vladislav; Simard, Olivier; Simic, Ljiljana; Simion, Stefan; Simioni, Eduard; Simmons, Brinick; Simoniello, Rosa; Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sivoklokov, Serguei; Siyad, Mohamed Jimcaale; Sjölin, Jörgen; Sjursen, Therese; Skinnari, Louise Anastasia; Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Smakhtin, Vladimir; Smart, Ben; Smestad, Lillian; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snidero, Giacomo; Snow, Joel; Snyder, Scott; Sobie, Randall; Socher, Felix; Soffer, Abner; Soh, Dart-yin; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Soloviev, Igor; Solovyanov, Oleg; Solovyev, Victor; Soni, Nitesh; Sood, Alexander; Sopko, Bruno; Sopko, Vit; Sorin, Veronica; Sosebee, Mark; Sotiropoulou, Calliope Louisa; Soualah, Rachik; Soueid, Paul; Soukharev, Andrey; South, David; Spagnolo, Stefania; Spanò, Francesco; Spearman, William Robert; Spighi, Roberto; Spigo, Giancarlo; Spiwoks, Ralf; Spousta, Martin; Spreitzer, Teresa; St Denis, Richard Dante; Stabile, Alberto; Stahlman, Jonathan; Staley, Richard; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanescu-Bellu, Madalina; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staszewski, Rafal; Steele, Genevieve; Steinbach, Peter; Steinberg, Peter; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stern, Sebastian; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoebe, Michael; Stoerig, Kathrin; Stoicea, Gabriel; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Strandberg, Jonas; Strandberg, Sara; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Stroynowski, Ryszard; Stucci, Stefania Antonia; Stugu, Bjarne; Stupak, John; Styles, Nicholas Adam; Su, Dong; Su, Jun; Subramania, Halasya Siva; Subramaniam, Rajivalochan; Succurro, Antonella; Sugaya, Yorihito; Suhr, Chad; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Sutton, Mark; Suzuki, Yu; Svatos, Michal; Swedish, Stephen; Swiatlowski, Maximilian; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Tackmann, Kerstin; Taenzer, Joe; Taffard, Anyes; Tafirout, Reda; Taghavirad, Saeed; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tam, Jason; Tamsett, Matthew; Tan, Kong Guan; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Shuji; Tanasijczuk, Andres Jorge; Tani, Kazutoshi; Tannoury, Nancy; Tapprogge, Stefan; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tavares Delgado, Ademar; Tayalati, Yahya; Taylor, Christopher; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teischinger, Florian Alfred; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thoma, Sascha; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thong, Wai Meng; Tian, Feng; Tibbetts, Mark James; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tiouchichine, Elodie; Tipton, Paul; Tisserant, Sylvain; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tollefson, Kirsten; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Tran, Huong Lan; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Tripiana, Martin; Triplett, Nathan; Trischuk, William; Trocmé, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trovatelli, Monica; True, Patrick; Trzebinski, Maciej; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsirintanis, Nikolaos; Tsiskaridze, Shota; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsung, Jieh-Wen; Tsuno, Soshi; Tsybychev, Dmitri; Tua, Alan; Tudorache, Alexandra; Tudorache, Valentina; Tuna, Alexander Naip; Tupputi, Salvatore; Turchikhin, Semen; Turecek, Daniel; Turra, Ruggero; Tuts, Michael; Twomey, Matthew Shaun; Tykhonov, Andrii; Tylmad, Maja; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ughetto, Michael; Ugland, Maren; Uhlenbrock, Mathias; Ukegawa, Fumihiko; Unal, Guillaume; Undrus, Alexander; Unel, Gokhan; Ungaro, Francesca; Unno, Yoshinobu; Urbaniec, Dustin; Urquijo, Phillip; Urrejola, Pedro; Usai, Giulio; Usanova, Anna; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Valencic, Nika; Valentinetti, Sara; Valero, Alberto; Valery, Loic; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; Van Der Deijl, Pieter; van der Geer, Rogier; van der Graaf, Harry; Van Der Leeuw, Robin; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; van Woerden, Marius Cornelis; Vanadia, Marco; Vandelli, Wainer; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Vardanyan, Gagik; Vari, Riccardo; Varnes, Erich; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vassilakopoulos, Vassilios; Vazeille, Francois; Vazquez Schroeder, Tamara; Veatch, Jason; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Venturini, Alessio; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Viazlo, Oleksandr; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Vieira De Souza, Julio; Viel, Simon; Vigne, Ralph; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinogradov, Vladimir; Virzi, Joseph; Vitells, Ofer; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vladoiu, Dan; Vlasak, Michal; Vogel, Adrian; Vokac, Petr; Volpi, Guido; Volpi, Matteo; von der Schmitt, Hans; von Radziewski, Holger; von Toerne, Eckhard; Vorobel, Vit; Vos, Marcel; Voss, Rudiger; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vu Anh, Tuan; Vuillermet, Raphael; Vukotic, Ilija; Vykydal, Zdenek; Wagner, Peter; Wagner, Wolfgang; Wahrmund, Sebastian; Wakabayashi, Jun; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wall, Richard; Waller, Peter; Walsh, Brian; Wang, Chao; Wang, Chiho; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Kuhan; Wang, Rui; Wang, Song-Ming; Wang, Tan; Wang, Xiaoxiao; Warburton, Andreas; Ward, Patricia; Wardrope, David Robert; Washbrook, Andrew; Wasicki, Christoph; Watanabe, Ippei; Watkins, Peter; Watson, Alan; Watson, Ian; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Ben; Webb, Samuel; Weber, Michele; Weber, Stefan Wolf; Webster, Jordan S; Weidberg, Anthony; Weigell, Philipp; Weingarten, Jens; Weiser, Christian; Weits, Hartger; Wells, Phillippa; Wenaus, Torre; Wendland, Dennis; Weng, Zhili; Wengler, Thorsten; Wenig, Siegfried; Wenzel, Volker; Wermes, Norbert; Werner, Matthias; Werner, Per; Wessels, Martin; Wetter, Jeffrey; Whalen, Kathleen; White, Andrew; White, Martin; White, Ryan; Whiteson, Daniel; Whittington, Denver; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik-Fuchs, Liv Antje Mari; Wijeratne, Peter Alexander; Wildauer, Andreas; Wildt, Martin Andre; Wilkens, Henric George; Will, Jonas Zacharias; Williams, Hugh; Williams, Sarah; Willocq, Stephane; Wilson, Alan; Wilson, John; Wingerter-Seez, Isabelle; Winkelmann, Stefan; Winklmeier, Frank; Wittgen, Matthias; Wittig, Tobias; Wittkowski, Josephine; Wollstadt, Simon Jakob; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wozniak, Krzysztof; Wraight, Kenneth; Wright, Michael; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wyatt, Terry Richard; Wynne, Benjamin; Xella, Stefania; Xiao, Meng; Xu, Da; Xu, Lailin; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamaguchi, Yohei; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamauchi, Katsuya; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Hongtao; Yang, Un-Ki; Yang, Yi; Yanush, Serguei; Yao, Liwen; Yasu, Yoshiji; Yatsenko, Elena; Yau Wong, Kaven Henry; Ye, Jingbo; Ye, Shuwei; Yen, Andy L; Yildirim, Eda; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Rikutaro; Yoshihara, Keisuke; Young, Charles; Young, Christopher John; Youssef, Saul; Yu, David Ren-Hwa; Yu, Jaehoon; Yu, Jiaming; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Zabinski, Bartlomiej; Zaidan, Remi; Zaitsev, Alexander; Zaman, Aungshuman; Zambito, Stefano; Zanello, Lucia; Zanzi, Daniele; Zaytsev, Alexander; Zeitnitz, Christian; Zeman, Martin; Zemla, Andrzej; Zengel, Keith; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhang, Dongliang; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Lei; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Zhengguo; Zhemchugov, Alexey; Zhong, Jiahang; Zhou, Bing; Zhou, Lei; Zhou, Ning; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zibell, Andre; Zieminska, Daria; Zimine, Nikolai; Zimmermann, Christoph; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Zinonos, Zinonas; Ziolkowski, Michael; Zobernig, Georg; Zoccoli, Antonio; zur Nedden, Martin; Zurzolo, Giovanni; Zutshi, Vishnu; Zwalinski, Lukasz; CERN. Geneva. The LHC experiments Committee; LHCC

    2013-01-01

    The Phase-I upgrade of the ATLAS Trigger and Data Acquisition (TDAQ) system is to allow the ATLAS experiment to efficiently trigger and record data at instantaneous luminosities that are up to three times that of the original LHC design while maintaining trigger thresholds close to those used in the initial run of the LHC.

  11. EXPERIENCE WITH SPLUNK FOR ARCHIVING AND VISUALISATION OF OPERATIONAL DATA IN ATLAS TDAQ SYSTEM

    CERN Document Server

    Kazarov, Andrei; The ATLAS collaboration

    2017-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) is a large, distributed system composed of several thousands interconnected computers and tens of thousands software processes (applications). Applications produce a large amount of operational messages at the order of 10$^{4}$ messages per second, which need to be reliably stored and delivered to TDAQ operators in a quasi real-time manner, and also be available for post-mortem analysis by experts. We have selected SPLUNK, a commercial solution by Splunk Inc, as an all-in-one solution for storing different types of operational data in an indexed database, and a web-based framework for searching and presenting the indexed data and for rapid development of user-oriented dashboards accessible in a web browser. The paper describes capabilities of the Splunk framework, use cases, applications and web dashboards developed for facilitating the browsing and searching of TDAQ operational data by TDAQ operators and experts.

  12. Experience with SPLUNK for archiving and visualization of operational data in ATLAS TDAQ system

    CERN Document Server

    Kazarov, Andrei; The ATLAS collaboration

    2018-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) is a large, distributed system composed of several thousands interconnected computers and tens of thousands software processes (applications). Applications produce a large amount of operational messages (at the order of O(10^4) messages per second), which need to be reliably stored and delivered to TDAQ operators in a realtime manner, and also be available for post-mortem analysis by experts. We have selected SPLUNK, a commercial solution by Splunk Inc, as a all-in-one solution for storing different types of operational data in an indexed database, and a web-based framework for searching and presenting the indexed data and for rapid development of user-oriented dashboards accessible in a web browser. The paper describes capabilities of Splunk framework, use cases, applications and web dashboards developed for facilitating the browsing and searching of TDAQ operational data by TDAQ operators and experts.

  13. Data-flow Performance Optimisation on Unreliable Networks: the ATLAS Data-Acquisition Case

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2015-01-01

    Abstract The ATLAS detector at CERN records proton-proton collisions delivered by the Large Hadron Collider (LHC). The ATLAS Trigger and Data-Acquisition (TDAQ) system identifies, selects, and stores interesting collision data. These are received from the detector readout electronics at an average rate of 100 kHz. The typical event data size is 1 to 2 MB. Overall, the ATLAS TDAQ can be seen as a distributed software system executed on a farm of roughly 2000 commodity PCs. The worker nodes are interconnected by an Ethernet network that at the restart of the LHC in 2015 is expected to experience a sustained throughput of several 10 GB/s. Abstract A particular type of challenge posed by this system, and by DAQ systems in general, is the inherently bursty nature of the data traffic from the readout buffers to the worker nodes. This can cause instantaneous network congestion and therefore performance degradation. The effect is particularly pronounced for unreliable network interconnections, such as Ethernet. Abstr...

  14. Data-flow performance optimization on unreliable networks: the ATLAS data-acquisition case

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2014-01-01

    The ATLAS detector at CERN records proton-proton collisions delivered by the Large Hadron Collider (LHC). The ATLAS Trigger and Data-Acquisition (TDAQ) system identifies, selects, and stores interesting collision data. These are received from the detector readout electronics at an average rate of 100 kHz. The typical event data size is 1 to 2 MB. Overall, the ATLAS TDAQ can be seen as a distributed software system executed on a farm of roughly 2000 commodity PCs. The worker nodes are interconnected by an Ethernet network that at the restart of the LHC in 2015 is expected to experience a sustained throughput of several 10 GB/s. A particular type of challenge posed by this system, and by DAQ systems in general, is the inherently bursty nature of the data traffic from the readout buffers to the worker nodes. This can cause instantaneous network congestion and therefore performance degradation. The effect is particularly pronounced for unreliable network interconnections, such as Ethernet. In this presentation we...

  15. The Error Reporting in the ATLAS TDAQ system

    CERN Document Server

    Kolos, S; The ATLAS collaboration; Papaevgeniou, L

    2014-01-01

    The ATLAS Error Reporting feature, which is used in the TDAQ environment, provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service(ERS), gives software applications the opportunity to collect and send comprehensive data about errors, happening at run-time, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the Error Reporting service as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data. The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When applications send information to ERS, depending on the actual configuration the information may end up in a local file, in a database, in distributed middle-ware, which can transport it to an expert system or dis...

  16. The Error Reporting in the ATLAS TDAQ System

    CERN Document Server

    Kolos, S; The ATLAS collaboration; Papaevgeniou, L

    2015-01-01

    The ATLAS Error Reporting feature, which is used in the TDAQ environment, provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service(ERS), gives software applications the opportunity to collect and send comprehensive data about errors, happening at run-time, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the Error Reporting service as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data. The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When applications send information to ERS, depending on the actual configuration the information may end up in a local file, in a database, in distributed middle-ware, which can transport it to an expert system or dis...

  17. Control in the ATLAS TDAQ System

    CERN Document Server

    Liko, D; Flammer, J; Dobson, M; Jones, R; Mapelli, L; Alexandrov, I; Korobov, S; Kotov, V; Mineev, M; Amorim, A; Fiuza de Barros, N; Klose, D; Pedro, L; Badescu, E; Caprini, M; Kolos, S; Kazarov, A; Ryabov, Yu; Soloviev, I; Computing In High Energy Physics

    2005-01-01

    TDAQ system requires a comprehensive and flexible control system. Its role ranges from the so-called run-control, e.g. starting and stopping the data taking, to error handling and fault tolerance. It also includes initialization and verification of the overall system. Following the traditional approach a hierarchical system of customizable controllers has been proposed. For the final system all functionality will be therefore available in a distributed manner, with the possibility of local customization. After a technology survey the open source expert system CLIPS has been chosen as a basis for the implementation of the supervision and the verification system. The CLIPS interpreter has been extended to provide a general control framework. Other ATLAS Online software components have been integrated as plug-ins and provide the mechanism for configuration and communication. Several components have been implemented sharing this technology. The dynamic behavior of the individual component is fully described by th...

  18. The Scaling Potential of an Optimized TDAQ System

    CERN Document Server

    Beck, H P

    2003-01-01

    The TDAQ Architecture has been defined and is described in the freshly submitted TDAQ TDR. The architecture described there is based on two possible deployment schemes for the Readout system and leaves a small number of fine-tuning parameters inherent to the architecture open for settlement in the post TDR phase of the project. This note tries to summarize these (few) open issues and shows how these could allow for an almost bottleneck-free architecture for Atlas TDAQ.

  19. Monitoring individual traffic flows within the ATLAS TDAQ network

    International Nuclear Information System (INIS)

    Sjoen, R; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A; Stancu, S; Ciobotaru, M

    2010-01-01

    The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities and limitations of this diagnostic tool, giving an example of its use in solving system problems that arise during the ATLAS data taking.

  20. Performance and evolution of the ATLAS TDAQ system with pp collisions at 7~TeV

    CERN Document Server

    Kono, T; The ATLAS collaboration

    2012-01-01

    During the data-taking period from 2009 until 2011, the ATLAS TDAQ system has been used very successfully to collect proton-proton data at LHC centre-of-mass energies between 900 GeV and 7 TeV. The TDAQ system is mostly made of off-the-shelf processing units organized in a farm of 2000 elements. The trigger system is designed in three levels reducing the event rate from the design bunch-crossing rate of 40 MHz to an average recording rate of about 300 Hz. Using custom electronics with input from the calorimeter and muon detectors, the first level rejects most background collisions in less than 2.5 $mu$s. The two following levels are software-based triggers with average decision times of 40 ms and 4 s respectively. The trigger system is designed to select events by identifying muons, electrons, photons, taus, jets, and B hadron candidates, as well as using global event signatures, such as missing transverse energy. In 2011, the TDAQ system has been operated with an overall efficiency of 94%, while meeting evol...

  1. Monitoring individual traffic flows within the ATLAS TDAQ network

    CERN Document Server

    Sjoen, R; Ciobotaru, M; Batraneanu, S M; Leahu, L; Martin, B; Al-Shabibi, A

    2010-01-01

    The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities a...

  2. Performance and evolution of the ATLAS TDAQ system with p-p collisions at 7 TeV

    CERN Document Server

    Kono, T; The ATLAS collaboration

    2012-01-01

    During the data taking period from 2009 until 2011, the ATLAS TDAQ system has been used very successfully to collect proton-proton data at LHC centre-of-mass energies between 900 GeV and 7 TeV. The TDAQ system is mostly made of off-the-shelf processing units organized in a farm of 2000 elements. The trigger system is designed in three levels reducing the event rate from the design bunch-crossing rate of 40 MHz to an average recording rate of about 300 Hz. Using custom electronics with input from the calorimeter and muon detectors, the first level rejects most background collisions in less than 2.5 us. The two following levels are software-based triggers with average decision times of 40 ms and 4 s respectively. The trigger system is designed to select events by identifying muons, electrons, photons, taus, jets, and B hadron candidates, as well as using global event signatures, such as missing transverse energy. In 2011, the TDAQ system has been operated with an overall efficiency of 94%, while meeting evolvin...

  3. TileCal TDAQ/DCS communication

    CERN Document Server

    Solans, C; Arabidze, G; Carneiro Ferreira, B; Sotto-Maior Peralva, B

    2007-01-01

    This document describes the communication between the TDAQ and DCS systems of the Hadronic Tile Calorimeter detector of the ATLAS experiment, currently under commissioning phase at CERN. It is a further step on the TDAQ and DCS communication for TileCal operation. The aim of the implementation is to increase the robustness and understanding of the detector from the two systems involved. The basic principle observed is that the two systems operate independently in parallel. Hence, the knowledge of the status of the whole detector from each of the two systems is required for further analysis of the archived data.

  4. Access Control in the ATLAS TDAQ Online Cluster

    CERN Document Server

    Leahu, Marius Constantin; Stoichescu, D A; Lehmann Miotto, G

    ATLAS (A Toroidal LHC Apparatus) is a general-purpose detector for studying high-energy particle interactions: it is the largest particle detector experiment at CERN and it is built around one of the interaction points of the proton beams accelerated by the Large Hadron Collider (LHC). The detector generates an impressive amount of raw data: 64 TB per second as a result of 40 MHz proton-proton collision rate with 1.6 MB data for each such event. The handling of such data rate is managed by a three levels Trigger and Data Acquisition (TDAQ) system, which filters out the events not relevant from physics research point of view and selects in the end in the order of 1000 events per second to be stored for offline analyses. This system comprises a significant number of hardware devices, software applications and human personnel to supervise the experiment operation. Their protection against damages as a result of misuse and their optimized exploitation by avoiding the conflicting accesses to resources are key requ...

  5. A rule-based verification and control framework in ATLAS Trigger-DAQ

    CERN Document Server

    Kazarov, A; Lehmann-Miotto, G; Sloper, J E; Ryabov, Yu; Computing In High Energy and Nuclear Physics

    2007-01-01

    In order to meet the requirements of ATLAS data taking, the ATLAS Trigger-DAQ system is composed of O(1000) of applications running on more than 2600 computers in a network. With such system size, s/w and h/w failures are quite often. To minimize system downtime, the Trigger-DAQ control system shall include advanced verification and diagnostics facilities. The operator should use tests and expertise of the TDAQ and detectors developers in order to diagnose and recover from errors, if possible automatically. The TDAQ control system is built as a distributed tree of controllers, where behavior of each controller is defined in a rule-based language allowing easy customization. The control system also includes verification framework which allow users to develop and configure tests for any component in the system with different levels of complexity. It can be used as a stand-alone test facility for a small detector installation, as part of the general TDAQ initialization procedure, and for diagnosing the problems ...

  6. The ADAM project: a generic web interface for retrieval and display of ATLAS TDAQ information

    International Nuclear Information System (INIS)

    Harwood, A; Miotto, G Lehmann; Magnoni, L; Vandelli, W; Savu, D

    2012-01-01

    This paper describes a new approach to the visualization of information about the operation of the ATLAS Trigger and Data Acquisition system. ATLAS is one of the two general purpose detectors positioned along the Large Hadron Collider at CERN. Its data acquisition system consists of several thousand computers interconnected via multiple gigabit Ethernet networks, that are constantly monitored via different tools. Operational parameters ranging from the temperature of the computers to the network utilization are stored in several databases for later analysis. Although the ability to view these data-sets individually is already in place, currently there is no way to view this data together, in a uniform format, from one location. The ADAM project has been launched in order to overcome this limitation. It defines a uniform web interface to collect data from multiple providers that have different structures. It is capable of aggregating and correlating the data according to user defined criteria. Finally, it visualizes the collected data using a flexible and interactive front-end web system. Structurally, the project comprises of 3 main levels of the data collection cycle: The Level 0 represents the information sources within ATLAS. These providers do not store information in a uniform fashion. The first step of the project was to define a common interface with which to expose stored data. The interface designed for the project originates from the Google Data Protocol API. The idea is to allow read-only access to data providers, through HTTP requests similar in format to the SQL query structure. This provides a standardized way to access this different information sources within ATLAS. The Level 1 can be considered the engine of the system. The primary task of the Level 1 is to gather data from multiple data sources via the common interface, to correlate this data together, or over a defined time series, and expose the combined data as a whole to the Level 2 web

  7. The ADAM project: a generic web interface for retrieval and display of ATLAS TDAQ information

    Science.gov (United States)

    Harwood, A.; Lehmann Miotto, G.; Magnoni, L.; Vandelli, W.; Savu, D.

    2012-06-01

    This paper describes a new approach to the visualization of information about the operation of the ATLAS Trigger and Data Acquisition system. ATLAS is one of the two general purpose detectors positioned along the Large Hadron Collider at CERN. Its data acquisition system consists of several thousand computers interconnected via multiple gigabit Ethernet networks, that are constantly monitored via different tools. Operational parameters ranging from the temperature of the computers to the network utilization are stored in several databases for later analysis. Although the ability to view these data-sets individually is already in place, currently there is no way to view this data together, in a uniform format, from one location. The ADAM project has been launched in order to overcome this limitation. It defines a uniform web interface to collect data from multiple providers that have different structures. It is capable of aggregating and correlating the data according to user defined criteria. Finally, it visualizes the collected data using a flexible and interactive front-end web system. Structurally, the project comprises of 3 main levels of the data collection cycle: The Level 0 represents the information sources within ATLAS. These providers do not store information in a uniform fashion. The first step of the project was to define a common interface with which to expose stored data. The interface designed for the project originates from the Google Data Protocol API. The idea is to allow read-only access to data providers, through HTTP requests similar in format to the SQL query structure. This provides a standardized way to access this different information sources within ATLAS. The Level 1 can be considered the engine of the system. The primary task of the Level 1 is to gather data from multiple data sources via the common interface, to correlate this data together, or over a defined time series, and expose the combined data as a whole to the Level 2 web

  8. A persistent back-end for the ATLAS TDAQ online information service (P-BEAST)

    Science.gov (United States)

    Sicoe, Alexandru D.; Lehmann Miotto, Giovanna; Magnoni, Luca; Kolos, Serguei; Soloviev, Igor

    2012-06-01

    This paper describes P-BEAST, a highly scalable, highly available and durable system for archiving monitoring information of the trigger and data acquisition (TDAQ) system of the ATLAS experiment at CERN. Currently this consists of 20,000 applications running on 2,400 interconnected computers but it is foreseen to grow further in the near future. P-BEAST stores considerable amounts of monitoring information which would otherwise be lost. Making this data accessible, facilitates long term analysis and faster debugging. The novelty of this research consists of using a modern key-value storage technology (Cassandra) to satisfy the massive time series data rates, flexibility and scalability requirements entailed by the project. The loose schema allows the stored data to evolve seamlessly with the information flowing within the Information Service. An architectural overview of P-BEAST is presented alongside a discussion about the technologies considered as candidates for storing the data. The arguments which ultimately lead to choosing Cassandra are explained. Measurements taken during operation in production environment illustrate the data volume absorbed by the system and techniques for reducing the required Cassandra storage space overhead.

  9. A persistent back-end for the ATLAS TDAQ online information service (P-BEAST)

    International Nuclear Information System (INIS)

    Sicoe, Alexandru D; Miotto, Giovanna Lehmann; Magnoni, Luca; Kolos, Serguei; Soloviev, Igor

    2012-01-01

    This paper describes P-BEAST, a highly scalable, highly available and durable system for archiving monitoring information of the trigger and data acquisition (TDAQ) system of the ATLAS experiment at CERN. Currently this consists of 20,000 applications running on 2,400 interconnected computers but it is foreseen to grow further in the near future. P-BEAST stores considerable amounts of monitoring information which would otherwise be lost. Making this data accessible, facilitates long term analysis and faster debugging. The novelty of this research consists of using a modern key-value storage technology (Cassandra) to satisfy the massive time series data rates, flexibility and scalability requirements entailed by the project. The loose schema allows the stored data to evolve seamlessly with the information flowing within the Information Service. An architectural overview of P-BEAST is presented alongside a discussion about the technologies considered as candidates for storing the data. The arguments which ultimately lead to choosing Cassandra are explained. Measurements taken during operation in production environment illustrate the data volume absorbed by the system and techniques for reducing the required Cassandra storage space overhead.

  10. Design, Results, Evolution and Status of the ATLAS Simulation at Point1 Project

    Science.gov (United States)

    Ballestrero, S.; Batraneanu, S. M.; Brasolin, F.; Contescu, C.; Fazio, D.; Di Girolamo, A.; Lee, C. J.; Pozo Astigarraga, M. E.; Scannicchio, D. A.; Sedov, A.; Twomey, M. S.; Wang, F.; Zaytsev, A.

    2015-12-01

    During the LHC Long Shutdown 1 (LSI) period, that started in 2013, the Simulation at Point1 (Sim@P1) project takes advantage, in an opportunistic way, of the TDAQ (Trigger and Data Acquisition) HLT (High-Level Trigger) farm of the ATLAS experiment. This farm provides more than 1300 compute nodes, which are particularly suited for running event generation and Monte Carlo production jobs that are mostly CPU and not I/O bound. It is capable of running up to 2700 Virtual Machines (VMs) each with 8 CPU cores, for a total of up to 22000 parallel jobs. This contribution gives a review of the design, the results, and the evolution of the Sim@P1 project, operating a large scale OpenStack based virtualized platform deployed on top of the ATLAS TDAQ HLT farm computing resources. During LS1, Sim@P1 was one of the most productive ATLAS sites: it delivered more than 33 million CPU-hours and it generated more than 1.1 billion Monte Carlo events. The design aspects are presented: the virtualization platform exploited by Sim@P1 avoids interferences with TDAQ operations and it guarantees the security and the usability of the ATLAS private network. The cloud mechanism allows the separation of the needed support on both infrastructural (hardware, virtualization layer) and logical (Grid site support) levels. This paper focuses on the operational aspects of such a large system during the upcoming LHC Run 2 period: simple, reliable, and efficient tools are needed to quickly switch from Sim@P1 to TDAQ mode and back, to exploit the resources when they are not used for the data acquisition, even for short periods. The evolution of the central OpenStack infrastructure is described, as it was upgraded from Folsom to the Icehouse release, including the scalability issues addressed.

  11. Network based on statistical multiplexing for event selection and event builder systems in high energy physics experiments

    International Nuclear Information System (INIS)

    Calvet, D.

    2000-03-01

    Systems for on-line event selection in future high energy physics experiments will use advanced distributed computing techniques and will need high speed networks. After a brief description of projects at the Large Hadron Collider, the architectures initially proposed for the Trigger and Data AcQuisition (TD/DAQ) systems of ATLAS and CMS experiments are presented and analyzed. A new architecture for the ATLAS T/DAQ is introduced. Candidate network technologies for this system are described. This thesis focuses on ATM. A variety of network structures and topologies suited to partial and full event building are investigated. The need for efficient networking is shown. Optimization techniques for high speed messaging and their implementation on ATM components are described. Small scale demonstrator systems consisting of up to 48 computers (∼1:20 of the final level 2 trigger) connected via ATM are described. Performance results are presented. Extrapolation of measurements and evaluation of needs lead to a proposal of implementation for the main network of the ATLAS T/DAQ system. (author)

  12. Large scale access tests and online interfaces to ATLAS conditions databases

    International Nuclear Information System (INIS)

    Amorim, A; Lopes, L; Pereira, P; Simoes, J; Soloviev, I; Burckhart, D; Schmitt, J V D; Caprini, M; Kolos, S

    2008-01-01

    The access of the ATLAS Trigger and Data Acquisition (TDAQ) system to the ATLAS Conditions Databases sets strong reliability and performance requirements on the database storage and access infrastructures. Several applications were developed to support the integration of Conditions database access with the online services in TDAQ, including the interface to the Information Services (IS) and to the TDAQ Configuration Databases. The information storage requirements were the motivation for the ONline A Synchronous Interface to COOL (ONASIC) from the Information Service (IS) to LCG/COOL databases. ONASIC avoids the possible backpressure from Online Database servers by managing a local cache. In parallel, OKS2COOL was developed to store Configuration Databases into an Offline Database with history record. The DBStressor application was developed to test and stress the access to the Conditions database using the LCG/COOL interface while operating in an integrated way as a TDAQ application. The performance scaling of simultaneous Conditions database read accesses was studied in the context of the ATLAS High Level Trigger large computing farms. A large set of tests were performed involving up to 1000 computing nodes that simultaneously accessed the LCG central database server infrastructure at CERN

  13. The Third ATLAS ROD Workshop

    CERN Multimedia

    Poggioli, L.

    A new-style Workshop After two successful ATLAS ROD Workshops dedicated to the ROD hardware and held at the Geneva University in 1998 and in 2000, a new style Workshop took place at LAPP in Annecy on November 14-15, 2002. This time the Workshop was fully dedicated to the ROD-TDAQ integration and software in view of the near future integration activities of the final RODs for the detector assembly and commissioning. More precisely, the aim of this workshop was to get from the sub-detectors the parameters needed for T-DAQ, as well as status and plans from ROD builders. On the other hand, what was decided and assumed had to be stated (like EB decisions and URDs), and also support plans. The Workshop gathered about 70 participants from all ATLAS sub-detectors and the T-DAQ community. The quite dense agenda allowed nevertheless for many lively discussions, and for a dinner in the old town of Annecy. The Sessions The Workshop was organized in five main sessions: Assumptions and recommendations Sub-de...

  14. ATLAS Fact Sheet : To raise awareness of the ATLAS detector and collaboration on the LHC

    CERN Multimedia

    ATLAS Outreach

    2010-01-01

    Facts on the Detector, Calorimeters, Muon System, Inner Detector, Pixel Detector, Semiconductor Tracker, Transition Radiation Tracker,, Surface hall, Cavern, Detector, Magnet system, Solenoid, Toroid, Event rates, Physics processes, Supersymmetric particles, Comparing LHC with Cosmic rays, Heavy ion collisions, Trigger and Data Acquisition TDAQ, Computing, the LHC and the ATLAS collaboration. This fact sheet also contains images of ATLAS and the collaboration as well as a short list of videos on ATLAS available for viewing.

  15. Network based on statistical multiplexing for event selection and event builder systems in high energy physics experiments; Reseau a multiplexage statistique pour les systemes de selection et de reconstruction d'evenements dans les experiences de physique des hautes energies

    Energy Technology Data Exchange (ETDEWEB)

    Calvet, D

    2000-03-01

    Systems for on-line event selection in future high energy physics experiments will use advanced distributed computing techniques and will need high speed networks. After a brief description of projects at the Large Hadron Collider, the architectures initially proposed for the Trigger and Data AcQuisition (TD/DAQ) systems of ATLAS and CMS experiments are presented and analyzed. A new architecture for the ATLAS T/DAQ is introduced. Candidate network technologies for this system are described. This thesis focuses on ATM. A variety of network structures and topologies suited to partial and full event building are investigated. The need for efficient networking is shown. Optimization techniques for high speed messaging and their implementation on ATM components are described. Small scale demonstrator systems consisting of up to 48 computers ({approx}1:20 of the final level 2 trigger) connected via ATM are described. Performance results are presented. Extrapolation of measurements and evaluation of needs lead to a proposal of implementation for the main network of the ATLAS T/DAQ system. (author)

  16. Status of the AFP Project in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00224260; The ATLAS collaboration

    2017-01-01

    Status of the AFP project in the ATLAS experiment is given. In 2016 one arm of the AFP detector was installed and first data have been taken. In parallel with integration of the AFP subdetector into the ATLAS TDAQ nad DCS, beam tests and preparations for the installation of the 2nd arm are performed.

  17. Network based on statistical multiplexing for event selection and event builder systems in high energy physics experiments; Reseau a multiplexage statistique pour les systemes de selection et de reconstruction d'evenements dans les experiences de physique des hautes energies

    Energy Technology Data Exchange (ETDEWEB)

    Calvet, D

    2000-03-01

    Systems for on-line event selection in future high energy physics experiments will use advanced distributed computing techniques and will need high speed networks. After a brief description of projects at the Large Hadron Collider, the architectures initially proposed for the Trigger and Data AcQuisition (TD/DAQ) systems of ATLAS and CMS experiments are presented and analyzed. A new architecture for the ATLAS T/DAQ is introduced. Candidate network technologies for this system are described. This thesis focuses on ATM. A variety of network structures and topologies suited to partial and full event building are investigated. The need for efficient networking is shown. Optimization techniques for high speed messaging and their implementation on ATM components are described. Small scale demonstrator systems consisting of up to 48 computers ({approx}1:20 of the final level 2 trigger) connected via ATM are described. Performance results are presented. Extrapolation of measurements and evaluation of needs lead to a proposal of implementation for the main network of the ATLAS T/DAQ system. (author)

  18. The ATLAS Fast Tracker

    CERN Document Server

    Volpi, Guido; The ATLAS collaboration

    2015-01-01

    The use of tracking information at the trigger level in the LHC Run II period is crucial for the trigger an data acquisition (TDAQ) system. The tracking precision is in fact important to identify specific decay products of the Higgs boson or new phenomena, a well as to distinguish the contributions coming from many contemporary collisions that occur at every bunch crossing. However, the track reconstruction is among the most demanding tasks performed by the TDAQ computing farm; in fact, full reconstruction at full Level-1 trigger accept rate (100 KHz) is not possible. In order to overcome this limitation, the ATLAS experiment is planning the installation of a specific processor: the Fast Tracker (FTK), which is aimed at achieving this goal. The FTK is a pipeline of high performance electronic, based on custom and commercial devices, which is expected to reconstruct, with high resolution, the trajectories of charged tracks with a transverse momentum above 1 GeV, using the ATLAS inner tracker information. Patte...

  19. Detection of data taking anomalies for the ATLAS experiment

    CERN Document Server

    De Castro Vargas Fernandes, Julio; The ATLAS collaboration; Lehmann Miotto, Giovanna

    2015-01-01

    The physics signals produced by the ATLAS detector at the Large Hadron Collider (LHC) at CERN are acquired and selected by a distributed Trigger and Data AcQuistition (TDAQ) system, comprising a large number of hardware devices and software components. In this work, we focus on the problem of online detection of anomalies along the data taking period. Anomalies, in this context, are defined as an unexpected behaviour of the TDAQ system that result in a loss of data taking efficiency: the causes for those anomalies may come from the TDAQ itself or from external sources. While the TDAQ system operates, it publishes several useful information (trigger rates, dead times, memory usage…). Such information over time creates a set of time series that can be monitored in order to detect (and react to) problems (or anomalies). Here, we approach TDAQ operation monitoring through a data quality perspective, i.e, an anomaly is seen as a loss of quality (an outlier) and it is reported: this information can be used to rea...

  20. Integrating Networking into ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2018-01-01

    Networking is foundational to the ATLAS distributed infrastructure and there are many ongoing activities related to networking both within and outside of ATLAS. We will report on the progress in a number of areas exploring ATLAS's use of networking and our ability to monitor the network, analyze metrics from the network, and tune and optimize application and end-host parameters to make the most effective use of the network. Specific topics will include work on Open vSwitch for production systems, network analytics, FTS testing and tuning, and network problem alerting and alarming.

  1. Performance and Operational Experience with the Heterogeneous Farm of the ATLAS Trigger and Data Acquisition System

    CERN Document Server

    Garelli, N; The ATLAS collaboration; Vandelli, W

    2011-01-01

    The ATLAS trigger and data acquisition (TDAQ) is a distributed, multi trigger level, data-acquisition system, mostly made of off-the-shelf processing units organized in a farm. In its final configuration the system will account more than 2000 nodes, sporting heterogeneous capabilities and network connections, due to the TDAQ program for rolling expansions and upgrades. In this paper we present how we dealt with the farm heterogeneity during the proton-proton collisions of 2010 and 2011: a period characterized by changing working conditions, and constantly increasing LHC instantaneous luminosity. We describe a graphical tool to balance the computing-power and bandwidth sharing across the trigger farms, a data-flow monitoring daemon that provides high-level resource-aware data-flow operational information and the evolution of data-flow communication protocols.

  2. Prospects and Results from the AFP Detector in ATLAS

    CERN Document Server

    Gach, Grzegorz; The ATLAS collaboration

    2016-01-01

    Status of the AFP project in the ATLAS experiment is given. In 2016 one arm of the AFP detector was installed and first data have been taken. In parallel with integration of the AFP subdetector into the ATLAS TDAQ nad DCS, beam tests and preparations for the installation of the 2nd arm are performed.

  3. The evolution of the Trigger and Data Acquisition System in the ATLAS experiment

    CERN Document Server

    Krasznahorkay, A; The ATLAS collaboration

    2014-01-01

    The ATLAS experiment, aimed at recording the results of LHC proton-proton collisions, is upgrading its Trigger and Data Acquisition (TDAQ) system during the current LHC first long shutdown. The purpose of the upgrade is to add robustness and flexibility to the selection and the conveyance of the physics data, simplify the maintenance of the infrastructure, exploit new technologies and, overall, make ATLAS data-taking capable of dealing with increasing event rates. The TDAQ system used to date is organised in a three-level selection scheme, including a hardware-based first-level trigger and second- and third-level triggers implemented as separate software systems distributed on separate, commodity hardware nodes. While this architecture was successfully operated well beyond the original design goals, the accumulated experience stimulated interest to explore possible evolutions. We will also be upgrading the hardware of the TDAQ system by introducing new elements to it. For the high-level trigger, the current p...

  4. Online remote monitoring facilities for the ATLAS experiment

    CERN Document Server

    Kolos, S; The ATLAS collaboration; Feng, E; Hauser, R; Yakovlev, A; Zaytsev, A

    2011-01-01

    ATLAS is one of the 4 LHC experiments which started to be operated in the collisions mode in 2010. The ATLAS apparatus itself as well as the Trigger and the DAQ system are extremely complex facilities which have been built up by the collaboration including 144 institutes from 33 countries. The effective running of the experiment is supported by a large number of experts distributed all over the world. This paper describes the online remote monitoring system which has been developed in the ATLAS Trigger and DAQ(TDAQ) community in order to support efficient participation of the experts from remote institutes in the exploitation of the experiment. The facilities provided by the remote monitoring system are ranging from the WEB based access to the general status and data quality for the ongoing data taking session to the scalable service providing real-time mirroring of the detailed monitoring data from the experimental area to the dedicated computers in the CERN public network, where this data is made available ...

  5. Networks in ATLAS

    Science.gov (United States)

    McKee, Shawn; ATLAS Collaboration

    2017-10-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

  6. A Scalable and Reliable Message Transport Service for the ATLAS Trigger and Data Acquisition System

    CERN Document Server

    Kazarov, A; The ATLAS collaboration; Kolos, S; Lehmann Miotto, G; Soloviev, I

    2014-01-01

    The ATLAS Trigger and Data Acquisition (TDAQ) is a large distributed computing system composed of several thousands of interconnected computers and tens of thousands applications. During a run, TDAQ applications produce a lot of control and information messages with variable rates, addressed to TDAQ operators or to other applications. Reliable, fast and accurate delivery of the messages is important for the functioning of the whole TDAQ system. The Message Transport Service (MTS) provides facilities for the reliable transport, the filtering and the routing of the messages, basing on publish-subscribe-notify communication pattern with content-based message filtering. During the ongoing LHC shutdown, the MTS was re-implemented, taking into account important requirements like reliability, scalability and performance, handling of slow subscribers case and also simplicity of the design and the implementation. MTS uses CORBA middleware, a common layer for TDAQ infrastructure, and provides sending/subscribing APIs i...

  7. Prospects and Results from the AFP Detector in ATLAS

    CERN Document Server

    Gach, Grzegorz; The ATLAS collaboration

    2017-01-01

    In 2016 one arm of the AFP detector was installed and first data have been taken. In parallel with integration of the AFP subdetector into the ATLAS TDAQ and DCS systems, beam tests and preparations for the installation of the 2$^{\\textrm{nd}}$ arm are performed. In this report, a status of the AFP project in the ATLAS experiment is discussed.

  8. The ATLAS fast tracker processor design

    CERN Document Server

    Volpi, Guido; Albicocco, Pietro; Alison, John; Ancu, Lucian Stefan; Anderson, James; Andari, Nansi; Andreani, Alessandro; Andreazza, Attilio; Annovi, Alberto; Antonelli, Mario; Asbah, Needa; Atkinson, Markus; Baines, J; Barberio, Elisabetta; Beccherle, Roberto; Beretta, Matteo; Biesuz, Nicolo Vladi; Blair, R E; Bogdan, Mircea; Boveia, Antonio; Britzger, Daniel; Bryant, Partick; Burghgrave, Blake; Calderini, Giovanni; Camplani, Alessandra; Cavaliere, Viviana; Cavasinni, Vincenzo; Chakraborty, Dhiman; Chang, Philip; Cheng, Yangyang; Citraro, Saverio; Citterio, Mauro; Crescioli, Francesco; Dawe, Noel; Dell'Orso, Mauro; Donati, Simone; Dondero, Paolo; Drake, G; Gadomski, Szymon; Gatta, Mauro; Gentsos, Christos; Giannetti, Paola; Gkaitatzis, Stamatios; Gramling, Johanna; Howarth, James William; Iizawa, Tomoya; Ilic, Nikolina; Jiang, Zihao; Kaji, Toshiaki; Kasten, Michael; Kawaguchi, Yoshimasa; Kim, Young Kee; Kimura, Naoki; Klimkovich, Tatsiana; Kolb, Mathis; Kordas, K; Krizka, Karol; Kubota, T; Lanza, Agostino; Li, Ho Ling; Liberali, Valentino; Lisovyi, Mykhailo; Liu, Lulu; Love, Jeremy; Luciano, Pierluigi; Luongo, Carmela; Magalotti, Daniel; Maznas, Ioannis; Meroni, Chiara; Mitani, Takashi; Nasimi, Hikmat; Negri, Andrea; Neroutsos, Panos; Neubauer, Mark; Nikolaidis, Spiridon; Okumura, Y; Pandini, Carlo; Petridou, Chariclia; Piendibene, Marco; Proudfoot, James; Rados, Petar Kevin; Roda, Chiara; Rossi, Enrico; Sakurai, Yuki; Sampsonidis, Dimitrios; Saxon, James; Schmitt, Stefan; Schoening, Andre; Shochet, Mel; Shoijaii, Jafar; Soltveit, Hans Kristian; Sotiropoulou, Calliope-Louisa; Stabile, Alberto; Swiatlowski, Maximilian J; Tang, Fukun; Taylor, Pierre Thor Elliot; Testa, Marianna; Tompkins, Lauren; Vercesi, V; Wang, Rui; Watari, Ryutaro; Zhang, Jianhong; Zeng, Jian Cong; Zou, Rui; Bertolucci, Federico

    2015-01-01

    The extended use of tracking information at the trigger level in the LHC is crucial for the trigger and data acquisition (TDAQ) system to fulfill its task. Precise and fast tracking is important to identify specific decay products of the Higgs boson or new phenomena, as well as to distinguish the contributions coming from the many collisions that occur at every bunch crossing. However, track reconstruction is among the most demanding tasks performed by the TDAQ computing farm; in fact, complete reconstruction at full Level-1 trigger accept rate (100 kHz) is not possible. In order to overcome this limitation, the ATLAS experiment is planning the installation of a dedicated processor, the Fast Tracker (FTK), which is aimed at achieving this goal. The FTK is a pipeline of high performance electronics, based on custom and commercial devices, which is expected to reconstruct, with high resolution, the trajectories of charged-particle tracks with a transverse momentum above 1 GeV, using the ATLAS inner tracker info...

  9. Performance and operational experience with the heterogeneous farm of the ATLAS Trigger and Data Acquisition system.

    CERN Document Server

    Garelli, N; The ATLAS collaboration; Vandelli, W

    2011-01-01

    The ATLAS trigger and data acquisition (TDAQ) is a distributed, multi trigger level, data-acquisition system, mostly made of off-the-shelf processing units organized in a farm. In its final configuration the system will account more than 2000 nodes, sporting heterogeneous capabilities and network connectivities, due to the TDAQ program for rolling expansions and upgrades. In this paper we will present how we dealt with the farm heterogeneity during the proton-proton collisions of 2010 and 2011: a period characterized by changing working conditions, and constantly increasing LHC instantaneous luminosity. We will describe a graphical tool to show, control, modify and balance the computing-power and bandwidth sharing across the trigger farms, a data-flow monitoring daemon which provides a high-level resource-aware data-flow operational information, and the evolution of data-flow communication protocols.

  10. Evolution of the Trigger and Data Acquisition System for the ATLAS experiment

    CERN Document Server

    Negri, A; The ATLAS collaboration

    2012-01-01

    The ATLAS experiment at the Large Hadron Collider at CERN relies on a complex and highly distributed Trigger and Data Acquisition (TDAQ) system to gather and select particle collision data at unprecedented energy and rates. The TDAQ is composed of three levels which reduces the event rate from the design bunch-crossing rate of 40 MHz to an average event recording rate of about 200 Hz. The first part of this paper gives an overview of the operational performance of the DAQ system during 2011 and the first months of data taking in 2012. It describes how the flexibility inherent in the design of the system has be exploited to meet the changing needs of ATLAS data taking and in some cases push performance beyond the original design performance specification. The experience accumulated in the TDAQ system operation during these years stimulated also interest to explore possible evolutions, despite the success of the current design. One attractive direction is to merge three systems - the second trigger level (L2), ...

  11. The ATLAS TDAQ DataCollection Software

    CERN Document Server

    Haeberli, C; Pretzl, K

    2003-01-01

    The Large Hadron Collider, which is currently under construction at CERN near Geneva, will collide protons with a center-of-mass energy of 14TeV. This high energy offers the possibility to discover particles with masses on the TeV scale. Bunches of 1.15 10^11 protons will cross at a rate of 40 MHz. 23 proton-proton collisions will happen at every bunch-crossing, which results in a total proton-proton interaction rate of almost one GHz. The biggest part of these interactions do not contain new physics but mostly QCD background. Therefore the detectors to discovery physics, such as ATLAS, need to select the ~100 bunch-crossings with the biggest discovery potential out of the 40 10^6 bunch-crossings per second. In case of the ATLAS experiment this reduction will be achieved on a three level trigger system. The first level trigger runs on custom hardware, the two higher trigger levels run as software algorithms on farms of hundreds of commodity PCs. The second level trigger will run at a rate of up to 100 kHz on ...

  12. A Web-based Solution to Visualize Operational Monitoring Data in the Trigger and Data Acquisition System of the ATLAS Experiment at the LHC

    CERN Document Server

    Avolio, Giuseppe; The ATLAS collaboration; Lehmann Miotto, Giovanna; Soloviev, Igor

    2016-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider (LHC) at CERN is composed of a large number of distributed hardware and software components (about 3000 machines and more than 25000 applications) which, in a coordinated manner, provide the data-taking functionality of the overall system. During data taking runs, a huge flow of operational data is produced in order to constantly monitor the system and allow proper detection of anomalies or misbehaviors. In the ATLAS TDAQ system, operational data are archived and made available to applications by the P-Beast (Persistent Back-End for the Atlas Information System of TDAQ) service, implementing a custom time-series database. The possibility to efficiently visualize both real-time and historical operational data is a great asset for the online identification of problems and for any post-mortem analysis. This paper will present a web-based solution developed to achieve such a goal: the solution leverages the flexibili...

  13. ATLAS tile calorimeter cesium calibration control and analysis software

    International Nuclear Information System (INIS)

    Solovyanov, O; Solodkov, A; Starchenko, E; Karyukhin, A; Isaev, A; Shalanda, N

    2008-01-01

    An online control system to calibrate and monitor ATLAS Barrel hadronic calorimeter (TileCal) with a movable radioactive source, driven by liquid flow, is described. To read out and control the system an online software has been developed, using ATLAS TDAQ components like DVS (Diagnostic and Verification System) to verify the hardware before running, IS (Information Server) for data and status exchange between networked computers, and other components like DDC (DCS to DAQ Connection), to connect to PVSS-based slow control systems of Tile Calorimeter, high voltage and low voltage. A system of scripting facilities, based on Python language, is used to handle all the calibration and monitoring processes from hardware perspective to final data storage, including various abnormal situations. A QT based graphical user interface to display the status of the calibration system during the cesium source scan is described. The software for analysis of the detector response, using online data, is discussed. Performance of the system and first experience from the ATLAS pit are presented

  14. ATLAS tile calorimeter cesium calibration control and analysis software

    Energy Technology Data Exchange (ETDEWEB)

    Solovyanov, O; Solodkov, A; Starchenko, E; Karyukhin, A; Isaev, A; Shalanda, N [Institute for High Energy Physics, Protvino 142281 (Russian Federation)], E-mail: Oleg.Solovyanov@ihep.ru

    2008-07-01

    An online control system to calibrate and monitor ATLAS Barrel hadronic calorimeter (TileCal) with a movable radioactive source, driven by liquid flow, is described. To read out and control the system an online software has been developed, using ATLAS TDAQ components like DVS (Diagnostic and Verification System) to verify the hardware before running, IS (Information Server) for data and status exchange between networked computers, and other components like DDC (DCS to DAQ Connection), to connect to PVSS-based slow control systems of Tile Calorimeter, high voltage and low voltage. A system of scripting facilities, based on Python language, is used to handle all the calibration and monitoring processes from hardware perspective to final data storage, including various abnormal situations. A QT based graphical user interface to display the status of the calibration system during the cesium source scan is described. The software for analysis of the detector response, using online data, is discussed. Performance of the system and first experience from the ATLAS pit are presented.

  15. Intelligent operations of the data acquisition system of the ATLAS experiment at the LHC

    CERN Document Server

    Anders, G; The ATLAS collaboration; Lehmann Miotto, G; Magnoni, L

    2014-01-01

    The ATLAS experiment at the Large Hadron Collider at CERN relies on a complex and highly distributed Trigger and Data Acquisition (TDAQ) system to gather and select particle collision data obtained at unprecedented energy and rates. The TDAQ system is composed of a large number of hardware and software components (about 3000 machines and more than 15000 concurrent processes at the end of LHC’s Run 1) which in a coordinated manner provide the data-taking functionality of the overall system. The Run Control (RC) system is the component steering the data acquisition by starting and stopping processes and by carrying all data-taking elements through well-defined states in a coherent way (finite state machine pattern). The RC is organized as a hierarchical tree (run control tree) of run controllers following the functional de-composition into systems and sub-systems of the ATLAS detector. Given the size and complexity of the TDAQ system, errors and failures are bound to happen and must be dealt with. The data ac...

  16. New Persistent Back-End for the ATLAS Online Information Service

    CERN Document Server

    Soloviev, I; The ATLAS collaboration

    2014-01-01

    The Trigger and Data Acquisition (TDAQ) and detector systems of the ATLAS experiment deploy more than 3000 computers, running more than 15000 concurrent processes, to perform the selection, recording and monitoring of the proton collisions data in ATLAS. Most of these processes produce and share operational monitoring data used for inter-process communication and analysis of the systems. Few of these data are archived by dedicated applications into conditions and histogram databases. The rest of the data remained transient and lost at the end of a data taking session. To save these data for later, offline analysis of the quality of data taking and to help investigating the behavior of the system by experts, the first prototype of a new Persistent Back-End for the Atlas Information System of TDAQ (P-BEAST) was developed and deployed in the second half of 2012. The modern, distributed, and Java-based Cassandra database has been used as the storage technology and the CERN EOS for long-term storage. This paper pr...

  17. Online remote monitoring facilities for the ATLAS experiment

    CERN Document Server

    Kolos, S; The ATLAS collaboration; Feng, E; Hauser, R; Yakovlev, A; Zaytsev, A

    2010-01-01

    ATLAS is one of the 4 LHC experiments which started to be operated in the collisions mode in 2010. The ATLAS apparatus itself as well as the Trigger and the DAQ system are extremely complex facilities which have been built up by the collaboration including 144 institutes from 33 countries. The effective running of the experiment is supported by a large number of experts distributed all over the world. This paper describes the online remote monitoring system which has been developed in the ATLAS TDAQ community in order to support efficient participation of the experts from remote institutes in the exploitation of the experiment. The facilities provided by the remote monitoring system are ranging from the WEB based access to the general status and data quality for the ongoing data taking session to the scalable service providing real-time mirroring of the detailed monitoring data from the experimental area to the dedicated computers in the CERN public network, where this data is made available to remote users t...

  18. Characterizing, managing and monitoring the networks for the ATLAS data acquisition system

    CERN Document Server

    AUTHOR|(CDS)2068860

    2007-01-01

    Particle physics studies the constituents of matter and the interactions between them. Many of the elementary particles do not exist under normal circumstances in nature. However, they can be created and detected during energetic collisions of other particles, as is done in particle accelerators. The Large Hadron Collider (LHC) being built at CERN will be the world's largest circular particle accelerator, colliding protons at energies of 14 TeV. Only a very small fraction of the interactions will give raise to interesting phenomena. The collisions produced inside the accelerator are studied using particle detectors. ATLAS is one of the detectors built around the LHC accelerator ring. During its operation, it will generate a data stream of 64 Terabytes/s. A Trigger and Data Acquisition System (TDAQ) is connected to ATLAS -- its function is to acquire digitized data from the detector and apply trigger algorithms to identify the interesting events. Achieving this requires the power of over 2000 computers plus an...

  19. Verification and Diagnostics Framework in ATLAS Trigger/DAQ

    CERN Document Server

    Barczyk, M.; Caprini, M.; Da Silva Conceicao, J.; Dobson, M.; Flammer, J.; Jones, R.; Kazarov, A.; Kolos, S.; Liko, D.; Lucio, L.; Mapelli, L.; Soloviev, I.; Hart, R.; Amorim, A.; Klose, D.; Lima, J.; Pedro, J.; Wolters, H.; Badescu, E.; Alexandrov, I.; Kotov, V.; Mineev, M.; Ryabov, Yu.; Ryabov, Yu.

    2003-01-01

    Trigger and data acquisition (TDAQ) systems for modern HEP experiments are composed of thousands of hardware and software components depending on each other in a very complex manner. Typically, such systems are operated by non-expert shift operators, which are not aware of system functionality details. It is therefore necessary to help the operator to control the system and to minimize system down-time by providing knowledge-based facilities for automatic testing and verification of system components and also for error diagnostics and recovery. For this purpose, a verification and diagnostic framework was developed in the scope of ATLAS TDAQ. The verification functionality of the framework allows developers to configure simple low-level tests for any component in a TDAQ configuration. The test can be configured as one or more processes running on different hosts. The framework organizes tests in sequences, using knowledge about components hierarchy and dependencies, and allowing the operator to verify the fun...

  20. FELIX: the new detector readout system for the ATLAS experiment

    CERN Document Server

    Bauer, Kevin Thomas; The ATLAS collaboration

    2017-01-01

    Starting in 2018 during the planned shutdown of the LHC, the ATLAS experiment at CERN will be deploying new optical link technology (GigaBit Transceiver links) connecting the front end electronics. The Front-End LInk eXchange (FELIX) will provide an infrastructure for the new GBT links to connect to the rest of the Trigger and Data Acquisition (TDAQ) system. FELIX is a PC-based system designed to route data and commands to and from the GBT links and a Commercial Off-The Shelf (COTS) network. In this paper, the FELIX system is described and the design of the hardware prototype and core software is presented.

  1. ATLAS TDAQ/DCS Event filter : Supervision Requirements

    CERN Document Server

    Bee, C P; Meessen, C; Qian, Z; Touchard, F; Green, P; Pinfold, J L; Wheeler, S; Negri, A; Scannicchio, D A; Vercesi, V

    2002-01-01

    The second iteration of the Software Development Process of the ATLAS Event Filter has been launched. A summary of the design phase of the first iteration is given in the introduction. The document gives constraints, use cases, functional and non-functional requirements for the Supervision sub-system of the Event Filter.

  2. Experience with highly-parallel software for the storage system of the ATLAS Experiment at CERN

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2012-01-01

    The ATLAS experiment is observing proton-proton collisions delivered by the LHC accelerator. The ATLAS Trigger and Data Acquisition (TDAQ) system selects interesting events on-line in a three-level trigger system in order to store them at a budgeted rate of several hundred Hz. This paper focuses on the TDAQ data-logging system and in particular on the implementation and performance of a novel parallel software design. In this respect, the main challenge presented by the data-logging workload is the conflict between the largely parallel nature of the event processing, especially the recently introduced event compression, and the constraint of sequential file writing and checksum evaluation. This is further complicated by the necessity of operating in a fully data-driven mode, to cope with continuously evolving trigger and detector configurations. In this paper we report on the design of the new ATLAS on-line storage software. In particular we will discuss our development experience using recent concurrency-ori...

  3. The ADAM project: a generic web interface for retrieval and display of ATLAS TDAQ information.

    CERN Document Server

    Harwood, A; The ATLAS collaboration; Magnoni, L; Vandelli, W; Savu, D

    2011-01-01

    This paper describes a new approach to the visualization of stored information about the operation of the ATLAS Trigger and Data Acquisition system. ATLAS is one of the two general purpose detectors positioned along the Large Hadron Collider at CERN. Its data acquisition system consists of several thousand computers interconnected via multiple gigabit Ethernet networks, that are constantly monitored via different tools. Operational parameters ranging from the temperature of the computers to the network utilization are stored in several databases for later analysis. Although the ability to view these data-sets individually is already in place, currently there is no way to view this data together, in a uniform format, from one location. The ADAM project has been launched in order to overcome this limitation. It defines a uniform web interface to collect data from multiple providers that have different structures. It is capable of aggregating and correlating the data according to user defined criteria. Finally, ...

  4. ADAM Project – A generic web interface for retrieval and display of ATLAS TDAQ information.

    CERN Document Server

    Harwood, A; The ATLAS collaboration; Lehmann Miotto, G

    2011-01-01

    This paper describes a new approach to the visualization of stored information about the operation of the ATLAS Trigger and Data Acquisition system. ATLAS is one of the two general purpose detectors positioned along the Large Hadron Collider at CERN. Its data acquisition system consists of several thousand computers interconnected via multiple gigabit Ethernet networks, that are constantly monitored via different tools. Operational parameters ranging from the temperature of the computers, to the network utilization are stored in several databases for a posterior analysis. Although the ability to view these data-sets individually is already in place, there currently is no way to view this data together, in a uniform format, from one location. The ADAM project has been launched in order to overcome this limitation. It defines a uniform web interface to collect data from multiple diversely structured providers. It is capable of aggregating and correlating the data according to user defined criteria. Finally it v...

  5. Networks in ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2016-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  6. Networks in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00260714; The ATLAS collaboration

    2017-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  7. Design, Results, Evolution and Status of the ATLAS Simulation at Point1 Project

    CERN Document Server

    AUTHOR|(SzGeCERN)377840; Fressard-Batraneanu, Silvia Maria; Ballestrero, Sergio; Contescu, Alexandru Cristian; Fazio, Daniel; Di Girolamo, Alessandro; Lee, Christopher Jon; Pozo Astigarraga, Mikel Eukeni; Scannicchio, Diana; Sedov, Alexey; Twomey, Matthew Shaun; Wang, Fuquan; Zaytsev, Alexander

    2015-01-01

    Abstract. During the LHC Long Shutdown 1 period (LS1), that started in 2013, the Simulation at Point1 (Sim@P1) Project takes advantage, in an opportunistic way, of the TDAQ (Trigger and Data Acquisition) HLT (High Level Trigger) farm of the ATLAS experiment. This farm provides more than 1300 compute nodes, which are particularly suited for running event generation and Monte Carlo production jobs that are mostly CPU and not I/O bound. It is capable of running up to 2700 virtual machines (VMs) provided with 8 CPU cores each, for a total of up to 22000 parallel running jobs. This contribution gives a review of the design, the results, and the evolution of the Sim@P1 Project; operating a large scale OpenStack based virtualized platform deployed on top of the ATLAS TDAQ HLT farm computing resources. During LS1, Sim@P1 was one of the most productive ATLAS sites: it delivered more than 50 million CPU-hours and it generated more than 1.7 billion Monte Carlo events to various analysis communities. The design aspects a...

  8. Design, Results, Evolution and Status of the ATLAS simulation in Point1 project.

    CERN Document Server

    Ballestrero, Sergio; The ATLAS collaboration; Brasolin, Franco; Contescu, Alexandru Cristian; Fazio, Daniel; Di Girolamo, Alessandro; Lee, Christopher Jon; Pozo Astigarraga, Mikel Eukeni; Scannicchio, Diana; Sedov, Alexey; Twomey, Matthew Shaun; Wang, Fuquan; Zaytsev, Alexander

    2015-01-01

    During the LHC long shutdown period (LS1), that started in 2013, the simulation in Point1 (Sim@P1) project takes advantage in an opportunistic way of the trigger and data acquisition (TDAQ) farm of the ATLAS experiment. The farm provides more than 1500 computer nodes, and they are particularly suitable for running event generation and Monte Carlo production jobs that are mostly CPU and not I/O bound. It is capable of running up to 2500 virtual machines (VM) provided with 8 CPU cores each, for a total of up to 20000 parallel running jobs. This contribution gives a thorough review of the design, the results and the evolution of the Sim@P1 project operating a large scale Openstack based virtualized platform deployed on top of the ATLAS TDAQ farm computing resources. During LS1, Sim@P1 was one of the most productive GRID sites: it delivered more than 50 million CPU-hours and it generated more than 1.7 billion Monte Carlo events to various analysis communities within the ATLAS collaboration. The particular design ...

  9. Integration of the trigger and data acquisition systems in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Abolins, M [Michigan State University, Department of Physics and Astronomy, East Lansing, Michigan (United States); Adragna, P [Department of Physics, Queen Mary and Westfield College, University of London, London (United Kingdom); Aleksandrov, E; Aleksandrov, I [Joint Institute for Nuclear Research, Dubna (Russian Federation); Amorim, A [Laboratorio de Instrumentacao e Fisica Experimental, Lisboa (Portugal); Anderson, K [University of Chicago, Enrico Fermi Institute, Chicago, Illinois (United States); Anduaga, X [National University of La Plata, La Plata (United States); Aracena, I; Bartoldus, R [Stanford Linear Accelerator Center (SLAC), Stanford (United States); Asquith, L [Department of Physics and Astronomy, University College London, London (United Kingdom); Avolio, G; Backlund, S [European Laboratory for Particle Physics (CERN), Geneva (Switzerland); Badescu, E [National Institute for Physics and Nuclear Engineering, Institute of Atomic Physics, Bucharest (Romania); Baines, J [Rutherford Appleton Laboratory, Chilton, Didcot (United Kingdom); Beck, H P [Laboratory for High Energy Physics, University of Bern, Bern (Switzerland); Bee, C [Centre de Physique des Particules de Marseille, IN2P3-CNRS, Marseille (France); Bell, P [Department of Physics and Astronomy, University of Manchester, Manchester (United Kingdom); Bell, W H [Department of Physics and Astronomy, University of Glasgow, Glasgow (United Kingdom); Barria, P; Batreanu, S [and others

    2008-07-01

    During 2006 and the first half of 2007, the installation, integration and commissioning of trigger and data acquisition (TDAQ) equipment in the ATLAS experimental area have progressed. There have been a series of technical runs using the final components of the system already installed in the experimental area. Various tests have been run including ones where level 1 preselected simulated proton-proton events have been processed in a loop mode through the trigger and dataflow chains. The system included the readout buffers containing the events, event building, level 2 and event filter trigger algorithms. The scalability of the system with respect to the number of event building nodes used has been studied and quantities critical for the final system, such as trigger rates and event processing times, have been measured using different trigger algorithms as well as different TDAQ components. This paper presents the TDAQ architecture, the current status of the installation and commissioning and highlights the main test results that validate the system.

  10. Integration of the trigger and data acquisition systems in ATLAS

    International Nuclear Information System (INIS)

    Abolins, M; Adragna, P; Aleksandrov, E; Aleksandrov, I; Amorim, A; Anderson, K; Anduaga, X; Aracena, I; Bartoldus, R; Asquith, L; Avolio, G; Backlund, S; Badescu, E; Baines, J; Beck, H P; Bee, C; Bell, P; Bell, W H; Barria, P; Batreanu, S

    2008-01-01

    During 2006 and the first half of 2007, the installation, integration and commissioning of trigger and data acquisition (TDAQ) equipment in the ATLAS experimental area have progressed. There have been a series of technical runs using the final components of the system already installed in the experimental area. Various tests have been run including ones where level 1 preselected simulated proton-proton events have been processed in a loop mode through the trigger and dataflow chains. The system included the readout buffers containing the events, event building, level 2 and event filter trigger algorithms. The scalability of the system with respect to the number of event building nodes used has been studied and quantities critical for the final system, such as trigger rates and event processing times, have been measured using different trigger algorithms as well as different TDAQ components. This paper presents the TDAQ architecture, the current status of the installation and commissioning and highlights the main test results that validate the system

  11. Integration of the Trigger and Data Acquisition Systems in ATLAS

    International Nuclear Information System (INIS)

    Abolins, M.; Adragna, P.; Aleksandrov, E.; Aleksandrov, I.; Amorim, A.; Anderson, K.; Anduaga, X.; Aracena, I.; Asquith, L.; Avolio, G.; Backlund, S.; Badescu, E.; Baines, J.; Barria, P.; Bartoldus, R.; Batreanu, S.; Beck, H.P.; Bee, C.; Bell, P.; Bell, W.H.; Bellomo, M.

    2011-01-01

    During 2006 and the first half of 2007, the installation, integration and commissioning of trigger and data acquisition (TDAQ) equipment in the ATLAS experimental area have progressed. There have been a series of technical runs using the final components of the system already installed in the experimental area. Various tests have been run including ones where level 1 preselected simulated proton-proton events have been processed in a loop mode through the trigger and dataflow chains. The system included the readout buffers containing the events, event building, level 2 and event filter trigger algorithms. The scalability of the system with respect to the number of event building nodes used has been studied and quantities critical for the final system, such as trigger rates and event processing times, have been measured using different trigger algorithms as well as different TDAQ components. This paper presents the TDAQ architecture, the current status of the installation and commissioning and highlights the main test results that validate the system.

  12. Multi-Threaded Evolution of the Data-Logging System of the ATLAS Experiment at CERN

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2011-01-01

    The ATLAS experiment is currently observing proton-proton collisions delivered by the LHC accelerator at a centre of mass energy of 7 TeV with a peak luminosity of ~1033 cm-2 s-1. The ATLAS Trigger and Data Acquisition (TDAQ) system selects interesting events on-line in a three-level trigger system in order to store them at a budgeted rate of ~200 Hz for an event size of ~1.5 MB. This paper focuses on the TDAQ data-logging system. Its purpose is to receive events from the third level trigger, process them and stream the results into different raw data files according to the trigger decision. The data files are subsequently moved to the central mass storage facility at CERN. The system currently in production has been commissioned in 2007 and has been working smoothly since then. It is however based on an essentially single-threaded design that is anticipated not to cope with the increase in event rate and event size that is foreseen as part of the ATLAS and LHC upgrade programs. This design also severely limi...

  13. Multi-Threaded Evolution of the Data-Logging System of the ATLAS Experiment at CERN

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2011-01-01

    The ATLAS experiment observes proton-proton collisions delivered by the LHC accelerator at a centre of mass energy of 7 TeV with a peak luminosity of ~ 10^33 cm^-2 s^-1 in 2011. The ATLAS Trigger and Data Acquisition (TDAQ) system selects interesting events on-line in a three-level trigger system in order to store them at a budgeted average rate of ~ 400 Hz for an event size of ~1.2 MB. This paper focuses on the TDAQ data-logging system. Its purpose is to receive events from the third level trigger, process them and stream the data into different raw files according to the trigger decision. The system currently in production is based on an essentially single-threaded design that is anticipated not to cope with the increase in event rate and event size foreseen as part of the ATLAS and LHC upgrade programs. This design also severely limits the possibility of performing additional CPU-intensive tasks. Therefore, a novel design able to exploit the full power of multi-core architecture is needed. The main challen...

  14. ATLAS-Canada Network

    Energy Technology Data Exchange (ETDEWEB)

    Gable, I; Sobie, R J [HEPnet/Canada, Victoria, BC (Canada); Bedinelli, M; Butterworth, S; Groer, L; Kupchinsky, V [University of Toronto, Toronto, ON (Canada); Caron, B; McDonald, S; Payne, C [TRIUMF Laboratory, Vancouver, BC (Canada); Chambers, R [University of Alberta, Edmonton, AB (Canada); Fitzgerald, B [University of Victoria, Victoria, BC (Canada); Hatem, R; Marshall, P; Pobric, D [CANARIE Inc., Ottawa, ON (Canada); Maddalena, P; Mercure, P; Robertson, S; Rochefort, M [McGill University, Montreal, QC (Canada); McWilliam, D [BCNet, Vancouver, BC (Canada); Siegert, M [Simon Fraser University, Burnaby, BC (Canada)], E-mail: igable@uvic.ca (and others)

    2008-12-15

    The ATLAS-Canada computing model consists of a WLCG Tier-1 computing centre located at the TRIUMF Laboratory in Vancouver, Canada, and two distributed Tier-2 computing centres in eastern and western Canadian universities. The TRIUMF Tier-1 is connected to the CERN Tier-0 via a 10G dedicated circuit provided by CANARIE. The Canadian institutions hosting Tier-2 facilities are connected to TRIUMF via 1G lightpaths, and routing between Tier-2s occurs through TRIUMF. This paper discusses the architecture of the ATLAS-Canada network, the challenges of building the network, and the future plans.

  15. Evolution of the Trigger and Data Acquisition System in the ATLAS experiment

    CERN Document Server

    Kama, Sami; The ATLAS collaboration

    2012-01-01

    The ATLAS detector is designed to observe proton-proton collisions delivered by the LHC accelerator. The ATLAS Trigger and Data Acquisition (TDAQ) system is responsible for the selection and the conveyance of physics data, reducing the rate of stored events from the initial 40 MHz LHC frequency to several hundreds Hz. The TDAQ system is organised in a three-level selection scheme, including a hardware-based first-level trigger and second- and third-level triggers implemented as software systems distributed on commodity hardware nodes. The second-level trigger operates over limited regions of the detector, the so-called Regions-of-Interest (RoI). The last selection step deals instead with complete events. In the current design, the second and third trigger levels are separate systems. While this architecture was successfully operated well beyond the original design goals, the accumulated experience stimulated interest to explore possible evolutions. One attractive direction is to merge the second and third tri...

  16. Evolution of the Trigger and Data Acquisition System in the ATLAS experiment

    CERN Document Server

    Kama, S; The ATLAS collaboration

    2012-01-01

    The ATLAS detector is designed to observe proton-proton collisions delivered by the LHC accelerator. The ATLAS Trigger and Data Acquisition (TDAQ) system is responsible for the selection and the conveyance of physics data, reducing the rate of stored events from the initial $40\\MHz$ LHC frequency to several hundreds Hz. The TDAQ system is organized in a three-level selection scheme, including a hardware-based first-level trigger and second- and third-level triggers implemented as software systems distributed on commodity hardware nodes. The second-level trigger operates over limited regions of the detector, the so-called Regions-of-Interest (RoI). The last selection step deals instead with complete events. In the current design, the second and third trigger levels are separate systems. While this architecture was successfully operated well beyond the original design goals, the accumulated experience stimulated interest to explore possible evolutions. One attractive direction is to merge the second and third t...

  17. The Error Reporting in the ATLAS TDAQ System

    Science.gov (United States)

    Kolos, Serguei; Kazarov, Andrei; Papaevgeniou, Lykourgos

    2015-05-01

    The ATLAS Error Reporting provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service (ERS), gives to software applications the opportunity to collect and send comprehensive data about run-time errors, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the ERS as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data. The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When an application sends information to ERS, depending on the configuration, it may end up in a local file, a database, distributed middleware which can transport it to an expert system or display it to users. Thanks to the open framework design of ERS, new information destinations can be added at any moment without touching the reporting and receiving applications. The ERS Application Program Interface (API) is provided in three programming languages used in the ATLAS online environment: C++, Java and Python. All APIs use exceptions for error reporting but each of them exploits advanced features of a given language to simplify the end-user program writing. For example, as C++ lacks language support for exceptions, a number of macros have been designed to generate hierarchies of C++ exception classes at compile time. Using this approach a software developer can write a single line of code to generate a boilerplate code for a fully qualified C++ exception class declaration with arbitrary number of parameters and multiple constructors, which encapsulates all relevant static information about the given type of issues. When a corresponding error occurs at run time, the program just need to create an instance of that class passing relevant values to one

  18. The Evolution of the Trigger and Data Acquisition System in the ATLAS Experiment

    CERN Document Server

    Garelli, N; The ATLAS collaboration

    2014-01-01

    The ATLAS experiment, aimed at recording the results of LHC proton-proton collisions, is upgrading its Trigger and Data Acquisition (TDAQ) system during the current LHC first long shutdown. The purpose of such upgrade is to add robustness and flexibility to the selection and the conveyance of the physics data, simplify the maintenance of the infrastructure, exploit new technologies and, overall, make ATLAS data-taking capable of dealing with increasing event rates. \

  19. Readout and Trigger for the AFP Detector at the ATLAS Experiment

    CERN Document Server

    Kocian, Martin; The ATLAS collaboration

    2018-01-01

    AFP, the ATLAS Forward Proton consists of silicon detectors at 205 m and 217 m on each side of ATLAS. In 2016 two detectors in one side were installed. The FEI4 chips are read at 160 Mbps over the optical fibers. The DAQ system uses a FPGA board with Artix chip and a mezzanine card with RCE data processing module based on a Zynq chip with ARM processor running Linux. In this contribution we give an overview of the AFP detector with the commissioning steps taken to integrate with the ATLAS TDAQ. Furthermore first performance results are presented.

  20. ATLAS TDAQ/DCS Event Filter Event Handler Requirements

    CERN Document Server

    Bee, C P; Meessen, C; Qian, Z; Touchard, F; Green, P; Pinfold, J L; Wheeler, S; Negri, A; Scannicchio, D A; Vercesi, V

    2002-01-01

    The second iteration of the Software Development Process of the ATLAS Event Filter has been launched. A summary of the design phase of the first iteration is given in the introduction. The document gives constraints, use cases, functional and non-functional requirements for the Event Handler sub-system of the Event Filter.

  1. The evolution of the Trigger and Data Acquisition System in the ATLAS experiment

    CERN Document Server

    Krasznahorkay, A; The ATLAS collaboration

    2013-01-01

    The ATLAS experiment, aimed at recording the results of LHC proton-proton collisions, is upgrading its Trigger and Data Acquisition (TDAQ) system during the current LHC first long shutdown. The purpose of such upgrade is to add robustness and flexibility to the selection and the conveyance of the physics data, simplify the maintenance of the infrastructure, exploit new technologies and, overall, make ATLAS data-taking capable of dealing with increasing event rates. The TDAQ system used to date is organised in a three-level selection scheme, including a hardware-based first-level trigger and second- and third-level triggers implemented as separate software systems distributed on commodity hardware nodes. The second-level trigger operates over limited regions of the detector, the so-called Regions-of-Interest (RoI). The third-level trigger deals instead with complete events. While this architecture was successfully operated well beyond the original design goals, the accumulated experience stimulated interest to...

  2. FELIX: a PCIe based high-throughput approach for interfacing front-end and trigger electronics in the ATLAS upgrade framework

    CERN Document Server

    Chen, Kai; The ATLAS collaboration

    2016-01-01

    The ATLAS Phase-I upgrade requires a Trigger and Data Acquisition (TDAQ) system able to trigger and record data from up to three times the nominal LHC instantaneous luminosity. The FELIX system provides this in a scalable, detector agnostic and easily upgradeable way. It is a PC-based gateway, routing between custom radiation tolerant optical links from front-end electronics, via FPGA PCIe Gen3 cards, and a commodity switched Ethernet or InfiniBand network. FELIX enables reducing custom electronics in favor of software on commercial servers. The FELIX system, results of demonstrator, design and testing of prototype are described.

  3. ATLAS TDAQ System Integration and Commissioning

    CERN Document Server

    Negri, A

    2010-01-01

    The ATLAS detector will be exposed to proton proton collisions at a center of mass energy of 14 TeV with the bunch crossing rate of 40 MHz. A three-level trigger system has been designed to reduce this rate down to the level at which only interesting events are fully reconstructed. The level 1 trigger reduces the rate down to 75 kHz via custom-built electronics. The Region of Interest Builder delivers the Region of Interest records to the second level trigger which runs the selection algorithms with the commodity processors and brings the rate further down to ~ 3.5 kHz. Finally the Event Filter reduces the rate down to ~ 200 Hz for permanent storage. We review the trigger and data acquisition architecture and its in situ commissioning using almost full detectors. Results on system functionality and performance based on the cosmic data, early experience on LHC beam in 2008 and preselected simulated events are presented.

  4. A web-based solution to visualize operational monitoring data in the Trigger and Data Acquisition system of the ATLAS experiment at the LHC

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00210941; The ATLAS collaboration; D'Ascanio, Matteo; Lehmann-Miotto, Giovanna; Soloviev, Igor

    2017-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider at CERN is composed of a large number of distributed hardware and software components (about 3000 computers and more than 25000 applications) which, in a coordinated manner, provide the data-taking functionality of the overall system. During data taking runs, a huge flow of operational data is produced in order to constantly monitor the system and allow proper detection of anomalies or misbehaviours. In the ATLAS trigger and data acquisition system, operational data are archived and made available to applications by the P-BEAST (Persistent Back-End for the Atlas Information System of TDAQ) service, implementing a custom time-series database. The possibility to efficiently visualize both realtime and historical operational data is a great asset facilitating both online identification of problems and post-mortem analysis. This paper will present a web-based solution developed to achieve such a goal: the solution le...

  5. New ATLAS Software & Computing Organization

    CERN Multimedia

    Barberis, D

    Following the election by the ATLAS Collaboration Board of Dario Barberis (Genoa University/INFN) as Computing Coordinator and David Quarrie (LBNL) as Software Project Leader, it was considered necessary to modify the organization of the ATLAS Software & Computing ("S&C") project. The new organization is based upon the following principles: separation of the responsibilities for computing management from those of software development, with the appointment of a Computing Coordinator and a Software Project Leader who are both members of the Executive Board; hierarchical structure of responsibilities and reporting lines; coordination at all levels between TDAQ, S&C and Physics working groups; integration of the subdetector software development groups with the central S&C organization. A schematic diagram of the new organization can be seen in Fig.1. Figure 1: new ATLAS Software & Computing organization. Two Management Boards will help the Computing Coordinator and the Software Project...

  6. The new inter process communication middle-ware for the ATLAS Trigger and Data Acquisition system

    CERN Document Server

    Kolos, Serguei; The ATLAS collaboration

    2016-01-01

    The ATLAS Trigger & Data Acquisition (TDAQ) project was started almost twenty years ago with the aim of providing scalable distributed data collection system for the experiment. While the software dealing with physics data flow was implemented by directly using the low-level communication protocols, like TCP and UDP, the control and monitoring infrastructure services for the TDAQ system were implemented on top of the CORBA communication middle-ware. CORBA provides a high-level object oriented abstraction for the inter process communication, hiding communication complexity from the developers. This approach speeds up and simplifies development of communication services but incurs some extra cost in terms of performance and resources overhead. Our experience of using CORBA for control and monitoring data exchange in the distributed TDAQ system was very successful, mostly due to the outstanding quality of the CORBA brokers, which have been used in the project: omniORB for C++ and JacORB for Java. However, du...

  7. The ATLAS Glasgow Overview Week

    CERN Multimedia

    Richard Hawkings

    2007-01-01

    The ATLAS Overview Weeks always provide a good opportunity to see the status and progress throughout the experiment, and the July week at Glasgow University was no exception. The setting, amidst the traditional buildings of one of the UK's oldest universities, provided a nice counterpoint to all the cutting-edge research and technology being discussed. And despite predictions to the contrary, the weather at these northern latitudes was actually a great improvement on the previous few weeks in Geneva. The meeting sessions comprehensively covered the whole ATLAS project, from the subdetector and TDAQ systems and their commissioning, through to offline computing, analysis and physics. As a long-time ATLAS member who remembers plenary meetings in 1991 with 30 people drawing detector layouts on a whiteboard, the hardware and installation sessions were particularly impressive - to see how these dreams have been translated into 7000 tons of reality (and with attendant cabling, supports and services, which certainly...

  8. Novel, Highly-Parallel Software for the Online Storage System of the ATLAS Experiment at CERN: Design and Performances

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2012-01-01

    The ATLAS experiment observes proton-proton collisions delivered by the LHC accelerator at CERN. The ATLAS Trigger and Data Acquisition (TDAQ) system selects interesting events on-line in a three-level trigger system in order to store them at a budgeted rate of several hundred Hz, for an average event size of ~1.5 MB. This paper focuses on the TDAQ data-logging system and in particular on the implementation and performance of a novel SW design, reporting on the effort of exploiting the full power of recently installed multi-core hardware. In this respect, the main challenge presented by the data-logging workload is the conflict between the largely parallel nature of the event processing, including the recently introduced on-line event-compression, and the constraint of sequential file writing and checksum evaluation. This is further complicated by the necessity of operating in a fully data-driven mode, to cope with continuously evolving trigger and detector configurations. In this paper we report on the desig...

  9. Novel, Highly-Parallel Software for the Online Storage System of the ATLAS Experiment at CERN: Design and Performances

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2012-01-01

    Abstract--- The ATLAS experiment observes proton-proton collisions delivered by the LHC accelerator at CERN. The ATLAS Trigger and Data Acquisition (TDAQ) system selects interesting events on-line in a three-level trigger system in order to store them at a budgeted rate of several hundred Hz, for an average event size of ~1.5 MB. This paper focuses on the TDAQ data-logging system and in particular on the implementation and performance of a novel software design, reporting on the effort of exploiting the full power of multi-core hardware. In this respect, the main challenge presented by the data-logging workload is the conflict between the largely parallel nature of the event processing, including the recently introduced on-line event-compression, and the constraint of sequential file writing and checksum evaluation. This is further complicated by the necessity of operating in a fully data-driven mode, to cope with continuously evolving trigger and detector configurations. In this paper we will briefly discuss...

  10. A review of structural and functional brain networks: small world and atlas.

    Science.gov (United States)

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Moore, Philip; Zheng, Jiaxiang

    2015-03-01

    Brain networks can be divided into two categories: structural and functional networks. Many studies of neuroscience have reported that the complex brain networks are characterized by small-world or scale-free properties. The identification of nodes is the key factor in studying the properties of networks on the macro-, micro- or mesoscale in both structural and functional networks. In the study of brain networks, nodes are always determined by atlases. Therefore, the selection of atlases is critical, and appropriate atlases are helpful to combine the analyses of structural and functional networks. Currently, some problems still exist in the establishment or usage of atlases, which are often caused by the segmentation or the parcellation of the brain. We suggest that quantification of brain networks might be affected by the selection of atlases to a large extent. In the process of building atlases, the influences of single subjects and groups should be balanced. In this article, we focused on the effects of atlases on the analysis of brain networks and the improved divisions based on the tractography or connectivity in the parcellation of atlases.

  11. Evolving ATLAS Computing For Today’s Networks

    CERN Document Server

    Campana, S; The ATLAS collaboration; Jezequel, S; Negri, G; Serfon, C; Ueda, I

    2012-01-01

    The ATLAS computing infrastructure was designed many years ago based on the assumption of rather limited network connectivity between computing centres. ATLAS sites have been organized in a hierarchical model, where only a static subset of all possible network links can be exploited and a static subset of well connected sites (CERN and the T1s) can cover important functional roles such as hosting master copies of the data. The pragmatic adoption of such simplified approach, in respect of a more relaxed scenario interconnecting all sites, was very beneficial during the commissioning of the ATLAS distributed computing system and essential in reducing the operational cost during the first two years of LHC data taking. In the mean time, networks evolved far beyond this initial scenario: while a few countries are still poorly connected with the rest of the WLCG infrastructure, most of the ATLAS computing centres are now efficiently interlinked. Our operational experience in running the computing infrastructure in ...

  12. Experience with highly-parallel software for the storage system of the ATLAS Experiment at CERN

    CERN Document Server

    Colombo, T; The ATLAS collaboration

    2012-01-01

    The ATLAS experiment is observing proton-proton collisions delivered by the LHC accelerator at a centre of mass energy of 7 TeV. The ATLAS Trigger and Data Acquisition (TDAQ) system selects interesting events on-line in a three-level trigger system in order to store them at a budgeted rate of several hundred Hz, for an average event size of ~1.2 MB. This paper focuses on the TDAQ data-logging system and in particular on the implementation and performance of a novel SW design, reporting on the effort of exploiting the full power of recently installed multi-core hardware. In this respect, the main challenge presented by the data-logging workload is the conflict between the largely parallel nature of the event processing, especially the recently introduced on-line event-compression, and the constraint of sequential file writing and checksum evaluation. This is furtherly complicated by the necessity of operating in a fully data-driven mode, to cope with continuously evolving trigger and detector configurations. T...

  13. The ATLAS Data Flow System for Run 2

    CERN Document Server

    Kazarov, Andrei; The ATLAS collaboration

    2015-01-01

    After its first shutdown, the LHC will provide pp collisions with increased luminosity and energy. In the ATLAS experiment, the Trigger and Data Acquisition (TDAQ) system has been upgraded to deal with the increased event rates. The Data Flow (DF) element of the TDAQ is a distributed hardware and software system responsible for buffering and transporting event data from the readout system to the High Level Trigger (HLT) and to the event storage. The DF has been reshaped in order to profit from the technological progress and to maximize the flexibility and efficiency of the data selection process. The updated DF is radically different from the previous implementation both in terms of architecture and expected performance. The pre-existing two level software filtering, known as L2 and the Event Filter, and the Event Building are now merged into a single process, performing incremental data collection and analysis. This design has many advantages, among which are: the radical simplification of the architecture, ...

  14. The ATLAS Women's Network: one year of activities

    CERN Multimedia

    Paula Eerola

    The idea for an ATLAS Women's Network was born during the ATLAS overview week in October 2005, when a few of us discussed our experiences and were pondering about what we could do. We felt that it was important to increase the visibility of women working in ATLAS in order to make a better and more effective use of the ATLAS human resources, that is, make sure that women are duly included at all levels. Furthermore, it is our belief that making ATLAS a better working environment for female collaborators and other female co-workers will benefit both us and the collaboration as a whole. On the individual level, all of us thought that we could benefit from peer support and experience sharing, and an ATLAS Women's Network could facilitate this by developing contacts between the ATLAS Women in ATLAS Institutes worldwide. Finally, we thought that it was important to increase the number of women studying physics and working in the field of physics research by identifying gender barriers in the career paths of women i...

  15. FELIX: a PCIe based high-throughput approach for interfacing front-end and trigger electronics in the ATLAS Upgrade framework

    Science.gov (United States)

    Anderson, J.; Bauer, K.; Borga, A.; Boterenbrood, H.; Chen, H.; Chen, K.; Drake, G.; Dönszelmann, M.; Francis, D.; Guest, D.; Gorini, B.; Joos, M.; Lanni, F.; Lehmann Miotto, G.; Levinson, L.; Narevicius, J.; Panduro Vazquez, W.; Roich, A.; Ryu, S.; Schreuder, F.; Schumacher, J.; Vandelli, W.; Vermeulen, J.; Whiteson, D.; Wu, W.; Zhang, J.

    2016-12-01

    The ATLAS Phase-I upgrade (2019) requires a Trigger and Data Acquisition (TDAQ) system able to trigger and record data from up to three times the nominal LHC instantaneous luminosity. The Front-End LInk eXchange (FELIX) system provides an infrastructure to achieve this in a scalable, detector agnostic and easily upgradeable way. It is a PC-based gateway, interfacing custom radiation tolerant optical links from front-end electronics, via PCIe Gen3 cards, to a commodity switched Ethernet or InfiniBand network. FELIX enables reducing custom electronics in favour of software running on commercial servers. The FELIX system, the design of the PCIe prototype card and the integration test results are presented in this paper.

  16. FELIX: a PCIe based high-throughput approach for interfacing front-end and trigger electronics in the ATLAS Upgrade framework

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00015561; Bauer, Kevin Thomas; Borga, Andrea; Boterenbrood, Henk; Chen, Hucheng; Chen, Kai; Drake, Gary; Donszelmann, Mark; Francis, David; Guest, Daniel; Gorini, Benedetto; Joos, Markus; Lanni, Francesco; Lehmann Miotto, Giovanna; Levinson, Lorne; Narevicius, Julia; Panduro Vazquez, William; Roich, Alexander; Ryu, Soo; Schreuder, Frans Philip; Schumacher, Jorn; Vandelli, Wainer; Vermeulen, Jos; Whiteson, Daniel; Wu, Weihao; Zhang, Jinlong

    2016-01-01

    The ATLAS Phase-I upgrade (2018) requires a Trigger and Data Acquisition (TDAQ) system able to trigger and record data from up to three times the nominal LHC instantaneous luminosity. The Front-End LInk eXchange (FELIX) system provides an infrastructure to achieve this in a scalable, detector agnostic and easily upgradeable way. It is a PC-based gateway, interfacing custom radiation tolerant optical links from front-end electronics, via FPGA PCIe Gen3 cards, to a commodity switched Ethernet or InfiniBand network. FELIX enables reducing custom electronics in favour of software running on commercial servers. The FELIX system, the design of the PCIe prototype card and the integration test results are presented in this paper.

  17. FELIX: a PCIe based high-throughput approach for interfacing front-end and trigger electronics in the ATLAS Upgrade framework

    International Nuclear Information System (INIS)

    Anderson, J.; Drake, G.; Ryu, S.; Bauer, K.; Guest, D.; Borga, A.; Boterenbrood, H.; Schreuder, F.; Chen, H.; Chen, K.; Lanni, F.; Dönszelmann, M.; Francis, D.; Gorini, B.; Joos, M.; Miotto, G. Lehmann; Levinson, L.; Narevicius, J.; Roich, A.; Vazquez, W. Panduro

    2016-01-01

    The ATLAS Phase-I upgrade (2019) requires a Trigger and Data Acquisition (TDAQ) system able to trigger and record data from up to three times the nominal LHC instantaneous luminosity. The Front-End LInk eXchange (FELIX) system provides an infrastructure to achieve this in a scalable, detector agnostic and easily upgradeable way. It is a PC-based gateway, interfacing custom radiation tolerant optical links from front-end electronics, via PCIe Gen3 cards, to a commodity switched Ethernet or InfiniBand network. FELIX enables reducing custom electronics in favour of software running on commercial servers. The FELIX system, the design of the PCIe prototype card and the integration test results are presented in this paper.

  18. The ATLAS Data Flow System for LHC Run II

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00305920; The ATLAS collaboration

    2016-01-01

    After its first shutdown, the LHC will provide pp collisions with increased luminosity and energy. In the ATLAS experiment, the Trigger and Data Acquisition (TDAQ) system has been upgraded to deal with the increased event rates. The Data Flow (DF) element of the TDAQ is a distributed hardware and software system responsible for buffering and transporting event data from the readout system to the High Level Trigger (HLT) and to the event storage. The DF has been reshaped in order to profit from the technological progress and to maximize the flexibility and efficiency of the data selection process. The updated DF is radically different from the previous implementation both in terms of architecture and expected performance. The pre-existing two level software filtering, known as L2 and the Event Filter, and the Event Building are now merged into a single process, performing incremental data collection and analysis. This design has many advantages, among which are: the radical simplification of the architecture, ...

  19. High-performance scalable Information Service for the ATLAS experiment

    CERN Document Server

    Kolos, S; The ATLAS collaboration; Hauser, R

    2012-01-01

    The ATLAS experiment is being operated by highly distributed computing system which is constantly producing a lot of status information which is used to monitor the experiment operational conditions as well as to access the quality of the physics data being taken. For example the ATLAS High Level Trigger(HLT) algorithms are executed on the online computing farm consisting from about 1500 nodes. Each HLT algorithm is producing few thousands histograms, which have to be integrated over the whole farm and carefully analyzed in order to properly tune the event rejection. In order to handle such non-physics data the Information Service (IS) facility has been developed in the scope of the ATLAS TDAQ project. The IS provides high-performance scalable solution for information exchange in distributed environment. In the course of an ATLAS data taking session the IS handles about hundred gigabytes of information which is being constantly updated with the update interval varying from a second to few tens of seconds. IS ...

  20. The LUCID detector ATLAS luminosity monitor and its electronic system

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00378808; The ATLAS collaboration

    2016-01-01

    Starting from 2015 LHC is performing a new run, at higher center of mass energy (13 TeV) and with 25 ns bunch-spacing. The ATLAS luminosity monitor LUCID has been completely renewed, both on detector design and in the electronics, in order to cope with the new running conditions. The new detector electronics is presented, featuring a new read-out board (LUCROD), for signal acquisition and digitization, PMT-charge integration and single-side luminosity measurements, and the revisited LUMAT board for side-A-side-C combination. The contribution covers the new boards design, the firmware and software developments, the implementation of luminosity algorithms, the optical communication between boards and the integration into the ATLAS TDAQ system.

  1. The ATLAS Data Flow system for the Second LHC Run

    CERN Document Server

    Hauser, Reiner; The ATLAS collaboration

    2015-01-01

    After its first shutdown, LHC will provide pp collisions with increased luminosity and energy. In the ATLAS experiment the Trigger and Data Acquisition (TDAQ) system has been upgraded to deal with the increased event rates. The Data Flow (DF) element of the TDAQ is a distributed hardware and software system responsible for buffering and transporting event data from the Readout system to the High Level Trigger (HLT) and to the event storage. The DF has been reshaped in order to profit from the technological progress and to maximize the flexibility and efficiency of the data selection process. The updated DF is radically different from the previous implementation both in terms of architecture and expected performance. The pre-existing two level software filtering, known as L2 and the Event Filter, and the Event Building are now merged into a single process, performing incremental data collection and analysis. This design has many advantages, among which are: the radical simplification of the architecture, the f...

  2. A Neural Network Approach to Muon Triggering in ATLAS

    CERN Document Server

    Livneh, Ran; CERN. Geneva

    2007-01-01

    The extremely high rate of events that will be produced in the future Large Hadron Collider requires the triggering mechanism to make precise decisions in a few nano-seconds. This poses a complicated inverse problem, arising from the inhomogeneous nature of the magnetic fields in ATLAS. This thesis presents a study of an application of Artificial Neural Networks to the muon triggering problem in the ATLAS end-cap. A comparison with realistic results from the ATLAS first level trigger simulation was in favour of the neural network, but this is mainly due to superior resolution available off-line. Other options for applying a neural network to this problem are discussed.

  3. Remote control of ATLAS-MPX Network and Data Visualization

    International Nuclear Information System (INIS)

    Turecek, D.; Holy, T.; Pospisil, S.; Vykydal, Z.

    2011-01-01

    The ATLAS-MPX Network is a network of 15 Medipix2-based detector devices, installed in various positions in the ATLAS detector at CERN, Geneva. The aim of the network is to perform a real-time measurement of the spectral characteristics and the composition of radiation inside the ATLAS detector during its operation. The remote control system of ATLAS-MPX controls and configures all the devices from one place, via a web interface, accessible from different operating systems. The Data Visualization application, also with a web interface, has been developed in order to present measured data to the scientific community. It allows to browse through recorded frames from all devices and to search for specific frames by date and time. Charts containing the number of different types of tracks in each frame as a function of time may be rendered from the database.

  4. High-Performance Scalable Information Service for the ATLAS Experiment

    International Nuclear Information System (INIS)

    Kolos, S; Boutsioukis, G; Hauser, R

    2012-01-01

    The ATLAS[1] experiment is operated by a highly distributed computing system which is constantly producing a lot of status information which is used to monitor the experiment operational conditions as well as to assess the quality of the physics data being taken. For example the ATLAS High Level Trigger(HLT) algorithms are executed on the online computing farm consisting from about 1500 nodes. Each HLT algorithm is producing few thousands histograms, which have to be integrated over the whole farm and carefully analyzed in order to properly tune the event rejection. In order to handle such non-physics data the Information Service (IS) facility has been developed in the scope of the ATLAS Trigger and Data Acquisition (TDAQ)[2] project. The IS provides a high-performance scalable solution for information exchange in distributed environment. In the course of an ATLAS data taking session the IS handles about a hundred gigabytes of information which is being constantly updated with the update interval varying from a second to a few tens of seconds. IS provides access to any information item on request as well as distributing notification to all the information subscribers. In the latter case IS subscribers receive information within a few milliseconds after it was updated. IS can handle arbitrary types of information, including histograms produced by the HLT applications, and provides C++, Java and Python API. The Information Service is a unique source of information for the majority of the online monitoring analysis and GUI applications used to control and monitor the ATLAS experiment. Information Service provides streaming functionality allowing efficient replication of all or part of the managed information. This functionality is used to duplicate the subset of the ATLAS monitoring data to the CERN public network with a latency of a few milliseconds, allowing efficient real-time monitoring of the data taking from outside the protected ATLAS network. Each information

  5. The ATLAS Trigger algorithms upgrade and performance in Run 2

    CERN Document Server

    Bernius, Catrin; The ATLAS collaboration

    2017-01-01

    Title: The ATLAS Trigger algorithms upgrade and performance in Run 2 (TDAQ) The ATLAS trigger has been used very successfully for the online event selection during the first part of the second LHC run (Run-2) in 2015/16 at a center-of-mass energy of 13 TeV. The trigger system is composed of a hardware Level-1 trigger and a software-based high-level trigger; it reduces the event rate from the bunch-crossing rate of 40 MHz to an average recording rate of about 1 kHz. The excellent performance of the ATLAS trigger has been vital for the ATLAS physics program of Run-2, selecting interesting collision events for wide variety of physics signatures with high efficiency. The trigger selection capabilities of ATLAS during Run-2 have been significantly improved compared to Run-1, in order to cope with the higher event rates and pile-up which are the result of the almost doubling of the center-of-mass collision energy and the increase in the instantaneous luminosity of the LHC. At the Level-1 trigger the undertaken impr...

  6. 17 April 2008 - Head of Internal Audit Network meeting visiting the ATLAS experimental area with CERN ATLAS Team Leader P. Fassnacht, ATLAS Technical Coordinator M. Nessi and ATLAS Resources Manager M. Nordberg.

    CERN Multimedia

    Mona Schweizer

    2008-01-01

    17 April 2008 - Head of Internal Audit Network meeting visiting the ATLAS experimental area with CERN ATLAS Team Leader P. Fassnacht, ATLAS Technical Coordinator M. Nessi and ATLAS Resources Manager M. Nordberg.

  7. Robustness of the ATLAS pixel clustering neural network algorithm

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration

    2016-01-01

    Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. In the ATLAS track reconstruction algorithm, an artificial neural network is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The robustness of the neural network algorithm is presented, probing its sensitivity to uncertainties in the detector conditions. The robustness is studied by evaluating the stability of the algorithm's performance under a range of variations in the inputs to the neural networks. Within reasonable variation magnitudes, the neural networks prove to be robust to most variation types.

  8. The TDAQ Baseline Architecture

    CERN Multimedia

    Wickens, F J

    The Trigger-DAQ community is currently busy preparing material for the DAQ, HLT and DCS TDR. Over the last few weeks a very important step has been a series of meetings to complete agreement on the baseline architecture. An overview of the architecture indicating some of the main parameters is shown in figure 1. As reported at the ATLAS Plenary during the February ATLAS week, the main area where the baseline had not yet been agreed was around the Read-Out System (ROS) and details in the DataFlow. The agreed architecture has: Read-Out Links (ROLs) from the RODs using S-Link; Read-Out Buffers (ROB) sited near the RODs, mounted in a chassis - today assumed to be a PC, using PCI bus at least for configuration, control and monitoring. The baseline assumes data aggregation, in the ROB and/or at the output (which could either be over a bus or in the network). Optimization of the data aggregation will be made in the coming months, but the current model has each ROB card receiving input from 4 ROLs, and 3 such c...

  9. Evolution and experience with the ATLAS Simulation at Point1 Project

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00389536; The ATLAS collaboration; Brasolin, Franco; Kouba, Tomas; Schovancova, Jaroslava; Fazio, Daniel; Di Girolamo, Alessandro; Scannicchio, Diana; Twomey, Matthew Shaun; Wang, Fuquan; Zaytsev, Alexander; Lee, Christopher

    2017-01-01

    The Simulation at Point1 project is successfully running standard ATLAS simulation jobs on the TDAQ HLT resources. The pool of available resources changes dynamically, therefore we need to be very effective in exploiting the available computing cycles. We present our experience with using the Event Service that provides the event-level granularity of computations. We show the design decisions and overhead time related to the usage of the Event Service. The improved utilization of the resources is also presented with the recent development in monitoring, automatic alerting, deployment and GUI.

  10. Evolution and experience with the ATLAS simulation at Point1 project

    CERN Document Server

    Ballestrero, Sergio; The ATLAS collaboration; Fazio, Daniel; Di Girolamo, Alessandro; Kouba, Tomas; Lee, Christopher; Scannicchio, Diana; Schovancova, Jaroslava; Twomey, Matthew Shaun; Wang, Fuquan; Zaytsev, Alexander

    2016-01-01

    The Simulation at Point1 project is successfully running traditional ATLAS simulation jobs on the TDAQ HLT resources. The pool of available resources changes dynamically, therefore we need to be very effective in exploiting the available computing cycles. We will present our experience with using the Event Service that provides the event-level granularity of computations. We will show the design decisions and overhead time related to the usage of the Event Service. The improved utilization of the resources will also be presented with the recent development in monitoring, automatic alerting, deployment and GUI.

  11. Development and test of the DAQ system for a Micromegas prototype installed into the ATLAS experiment

    CERN Document Server

    Zibell, Andre; The ATLAS collaboration; Bianco, Michele; Martoiu, Victor Sorin

    2015-01-01

    A Micromegas (MM) quadruplet prototype with an active area of 0.5 m$^2$ that adopts the general design foreseen for the upgrade of the innermost forward muon tracking systems (Small Wheels) of the ATLAS detector in 2018-2019, has been built at CERN and is going to be tested in the ATLAS cavern environment during the LHC RUN-II period 2015-2017. The integration of this prototype detector into the ATLAS data acquisition system using custom ATCA equipment is presented. An ATLAS compatible ReadOutDriver (ROD) based on the Scalable Readout System (SRS), the Scalable Readout Unit (SRU), will be used in order to transmit the data after generating valid event fragments to the high-level Read Out System (ROS). The SRU will be synchronized with the LHC bunch crossing clock (40.08 MHz) and will receive the Level-1 trigger signals from the Central Trigger Processor (CTP) through the TTCrx receiver ASIC. The configuration of the system will be driven directly from the ATLAS Run Control System. By using the ATLAS TDAQ Soft...

  12. Test Management Framework for the ATLAS Experiment

    CERN Document Server

    Kazarov, Andrei; The ATLAS collaboration; Avolio, Giuseppe

    2018-01-01

    Test Management Framework for the Data Acquisition of the ATLAS Experiment Data Acquisition (DAQ) of the ATLAS experiment is a large distributed and inhomogeneous system: it consists of thousands of interconnected computers and electronics devices that operate coherently to read out and select relevant physics data. Advanced diagnostics capabilities of the TDAQ control system are a crucial feature which contributes significantly to smooth operation and fast recovery in case of the problems and, finally, to the high efficiency of the whole experiment. The base layer of the verification and diagnostic functionality is a test management framework. We have developed a flexible test management system that allows the experts to define and configure tests for different components, indicate follow-up actions to test failures and describe inter-dependencies between DAQ or detector elements. This development is based on the experience gained with the previous test system that was used during the first three years of th...

  13. The ATLAS Muon to Central Trigger Processor Interface Upgrade for the Run 3 of the LHC

    CERN Document Server

    Armbruster, Aaron James; The ATLAS collaboration; Chelstowska, Magda Anna

    2017-01-01

    To cope with the higher luminosity and physics cross-sections for the third run of the Large Hadron Collider (LHC) and beyond, the Trigger and Data Acquisition (TDAQ) system of ATLAS experiment at CERN is being upgraded. Part of the TDAQ system, the Muon to Central Trigger Processor Interface (MUCTPI) receives muon candidates information from each of the 208 barrel and endcap muon trigger sectors, counts muon candidates for each transverse momentum threshold and sends the result to the Central Trigger Processor (CTP). The MUCTPI takes into account the possible overlap between trigger sectors in order to avoid double counting of muon candidates. A full redesign and replacement of the existing MUCTPI is required in order to provide full-granularity muon position information at the bunch crossing rate to the Topological Trigger processor (L1Topo) and to be able to interface with the new sector logic modules. State-of-the-art FPGA technology and high-density ribbon fiber-optic transmitters and receivers is being...

  14. The ATLAS Muon-to-Central Trigger Processor Interface Upgrade for the Run 3 of the LHC

    CERN Document Server

    Armbruster, Aaron James; The ATLAS collaboration

    2017-01-01

    To cope with the higher luminosity and physics cross-sections for the third run of the Large Hadron Collider (LHC) and beyond, the Trigger and Data Acquisition (TDAQ) system of ATLAS experiment at CERN is being upgraded. Part of the TDAQ system, the Muon to Central Trigger Processor Interface (MUCTPI) receives muon candidates information from each of the 208 barrel and endcap muon trigger sectors, counts muon candidates for each transverse momentum threshold and sends the result to the Central Trigger Processor (CTP). The MUCTPI takes into account the possible overlap between trigger sectors in order to avoid double counting of muon candidates. A full redesign and replacement of the existing MUCTPI is required in order to provide full-granularity muon position information at the bunch crossing rate to the Topological Trigger processor (L1Topo) and to be able to interface with the new sector logic modules. State-of-the-art FPGA technology and high-density ribbon fiber-optic transmitters and receivers is being...

  15. ATLAS, CMS, LHCb and ALICE Career Networking Event 2015

    CERN Multimedia

    Marinov, Andrey; Strom, Derek Axel

    2015-01-01

    A networking event for alumni of the ATLAS, CMS, LHCb and ALICE experiments as well as current ATLAS/CMS/LHCb/ALICE postdocs and graduate students. This event offers an insight into career opportunities outside of academia. Various former members of the ATLAS, CMS, LHCb and ALICE collaborations will give presentations and be part of a panel discussion and elaborate on their experience in companies in a diverse range of fields (industry, finance, IT,...). Details at https://indico.cern.ch/event/440616

  16. Full system test of module to DAQ for ATLAS IBL

    Energy Technology Data Exchange (ETDEWEB)

    Behpour, Rouhina; Mattig, Peter; Wensing, Marius [Wuppertal University (Germany); Bindi, Marcello [Goettingen University (Germany)

    2015-07-01

    IBL (Insertable B Layer) as the inner most layer in the ATLAS detector at the LHC has been successfully integrated to the system last June 2014. IBL system reliability and consistency is under investigation during ongoing milestone runs at CERN. Back of Crate card (BOC) and Read out Driver (ROD) as two of the main electronic cards act as an interface between the IBL modules and the TDAQ chain. The detector data will be received and processed and then formatted by an interaction between these two electronic cards. The BOC takes advantage of using S-Link implementation inside the main FPGAs. The S-Link protocol as a standard high performance data acquisition link between the readout electronic cards and the TDAQ system is developed and used at CERN. It is based on the idea that detector formatted data will be transferred through optical fibers to the ROS (Read out System) PC for being stored via the ROBIN (Read out Buffer) cards. This talk presents the results that confirm a stable and good performance of the system, from the modules to the read out electronic cards and then to the ROS PCs via S-Link.

  17. Monitoring the US ATLAS Network Infrastructure with perfSONAR-PS

    International Nuclear Information System (INIS)

    McKee, Shawn; Lake, Andrew; Laurens, Philippe; Severini, Horst; Wlodek, Tomasz; Wolff, Stephen; Zurawski, Jason

    2012-01-01

    Global scientific collaborations, such as ATLAS, continue to push the network requirements envelope. Data movement in this collaboration is routinely including the regular exchange of petabytes of datasets between the collection and analysis facilities in the coming years. These requirements place a high emphasis on networks functioning at peak efficiency and availability; the lack thereof could mean critical delays in the overall scientific progress of distributed data-intensive experiments like ATLAS. Network operations staff routinely must deal with problems deep in the infrastructure; this may be as benign as replacing a failing piece of equipment, or as complex as dealing with a multi-domain path that is experiencing data loss. In either case, it is crucial that effective monitoring and performance analysis tools are available to ease the burden of management. We will report on our experiences deploying and using the perfSONAR-PS Performance Toolkit at ATLAS sites in the United States. This software creates a dedicated monitoring server, capable of collecting and performing a wide range of passive and active network measurements. Each independent instance is managed locally, but able to federate on a global scale; enabling a full view of the network infrastructure that spans domain boundaries. This information, available through web service interfaces, can easily be retrieved to create customized applications. The US ATLAS collaboration has developed a centralized “dashboard” offering network administrators, users, and decision makers the ability to see the performance of the network at a glance. The dashboard framework includes the ability to notify users (alarm) when problems are found, thus allowing rapid response to potential problems and making perfSONAR-PS crucial to the operation of our distributed computing infrastructure.

  18. Development and test of the DAQ system for a Micromegas prototype to be installed in the ATLAS experiment

    CERN Document Server

    Zibell, Andre; The ATLAS collaboration; Bianco, Michele; Martoiu, Victor Sorin

    2015-01-01

    A Micromegas (MM) quadruplet prototype with an active area of 0.5 m 2 that adopts the general design foreseen for the upgrade of the innermost forward muon tracking systems (Small Wheels) of the ATLAS detector in 2018-2019, has been built at CERN and is going to be tested in the ATLAS cavern environment during the LHC RUN-II period 2015-2017. The integration of this prototype detector into the ATLAS data acquisition system using custom ATCA equipment is presented. An ATLAS compatible Read Out Driver (ROD) based on the Scalable Readout System (SRS), the Scalable Readout Unit (SRU), will be used in order to transmit the data after generating valid event fragments to the high-level Read Out System (ROS). The SRU will be synchronized with the LHC bunch crossing clock (40.08 MHz) and will receive the Level-1 trigger signals from the Central Trigger Processor (CTP) through the TTCrx receiver ASIC. The configuration of the system will be driven directly from the ATLAS Run Control System. By using the ATLAS TDAQ Soft...

  19. The readiness of the ATLAS Trigger-DAQ system for the second LHC run

    CERN Document Server

    Rammensee, Michael; The ATLAS collaboration

    2015-01-01

    After its first shutdown, the Large Hadron Collider (LHC) will provide proton-proton collisions with increased luminosity and energy. In the ATLAS experiment~\\cite{Atlas}, the Trigger and Data Acquisition (TDAQ) system has been upgraded to deal with the increased event rates~\\cite{TDAQPhase1}. The updated system is radically different from the previous implementation, both in terms of architecture and expected performance. The main architecture has been reshaped in order to profit from the technological progress and to maximize the flexibility and efficiency of the data selection process. Design choices and the strategies employed to minimize the data-collection and the selection latency will be discussed. First results of tests done during the commissioning phase and the operational performance after the first months of data taking will be presented.

  20. Monitoring the US ATLAS Network Infrastructure with perfSONAR-PS

    CERN Document Server

    McKee, S; The ATLAS collaboration; Laurens, P; Severini, H; Wlodek, T; Wolff, S; Zurawski, J

    2012-01-01

    Global scientific collaborations, such as ATLAS, continue to push the network requirements envelope. Data movement in this collaboration is routinely including the regular exchange of petabytes of datasets between the collection and analysis facilities in the coming years. These requirements place a high emphasis on networks functioning at peak efficiency and availability; the lack thereof could mean critical delays in the overall scientific progress of distributed data-intensive experiments like ATLAS. Network operations staff routinely must deal with problems deep in the infrastructure; this may be as benign as replacing a failing piece of equipment, or as complex as dealing with a multidomain path that is experiencing data loss. In either case, it is crucial that effective monitoring and performance analysis tools are available to ease the burden of management. We will report on our experiences deploying and using the perfSONAR-PS Performance Toolkit[8] at ATLAS sites in the United States. This software cr...

  1. The Evolution of the Region of Interest Builder for the ATLAS Experiment at CERN

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00060668; Blair, Robert; Crone, Gordon Jeremy; Green, Barry; Love, Jeremy; Proudfoot, James; Rifki, Othmane; Panduro Vazquez, William; Vandelli, Wainer; Zhang, Jinlong

    2016-01-01

    ATLAS is a general purpose particle detector, at the Large Hadron Collider (LHC) at CERN, designed to measure the products of proton collisions. Given the high interaction rate (40 MHz), selective triggering in real time is required to reduce the rate to the experiment's data storage capacity (1 kHz). To meet this requirement, ATLAS employs a hardware trigger that reduces the rate to 100 kHz and software based triggers to select interesting interactions for physics analysis. The Region of Interest Builder (RoIB) is an essential part of the ATLAS detector Trigger and Data Acquisition (TDAQ) chain where the coordinates of the regions of interest (RoIs) identified by the first level trigger (L1) are collected and passed to the High Level Trigger (HLT) to make a decision. While the current custom VME based RoIB operated reliably during the first run of the LHC, it is desirable to have a more flexible RoIB and more operationally maintainable in the future, as the LHC reaches higher luminosity and ATLAS increases t...

  2. Automated load balancing in the ATLAS high-performance storage software

    CERN Document Server

    Le Goff, Fabrice; The ATLAS collaboration

    2017-01-01

    The ATLAS experiment collects proton-proton collision events delivered by the LHC accelerator at CERN. The ATLAS Trigger and Data Acquisition (TDAQ) system selects, transports and eventually records event data from the detector at several gigabytes per second. The data are recorded on transient storage before being delivered to permanent storage. The transient storage consists of high-performance direct-attached storage servers accounting for about 500 hard drives. The transient storage operates dedicated software in the form of a distributed multi-threaded application. The workload includes both CPU-demanding and IO-oriented tasks. This paper presents the original application threading model for this particular workload, discussing the load-sharing strategy among the available CPU cores. The limitations of this strategy were reached in 2016 due to changes in the trigger configuration involving a new data distribution pattern. We then describe a novel data-driven load-sharing strategy, designed to automatical...

  3. The Evolution of the Region of Interest Builder in the ATLAS Experiment

    CERN Document Server

    Blair, Robert; The ATLAS collaboration; Green, Barry; Love, Jeremy; Proudfoot, James; Rifki, Othmane; Panduro Vazquez, Jose Guillermo; Zhang, Jinlong

    2015-01-01

    ATLAS is a general purpose particle detector at the Large Hadron Collider (LHC) at CERN designed to measure the products of proton collisions. Given their high interaction rate (1GHz), selective triggering in real time is required to reduce the rate to the experiment’s data storage capacity (1KHz). To meet this requirement, ATLAS employs a combination of hardware and software triggers to select interesting collisions for physics analysis. The Region of Interest Builder (RoIB) is an integral part of the ATLAS detector Trigger and Data Acquisition (TDAQ) chain where the coordinates of the regions of interest (RoIs) identified by the first level trigger (L1) are collected and passed to the High Level Trigger (HLT) to make a decision. While the current custom RoIB operated reliably during the first run of the LHC, it is desirable to have the RoIB more operationally maintainable in the new run, which will reach higher luminosities with an increased complexity of L1 triggers. We are responsible for migrating the ...

  4. The Control and Configuration Software of the ATLAS Data Acquisition System: Upgrades for LHC Run 2

    CERN Document Server

    Aleksandrov, Igor; The ATLAS collaboration; Avolio, Giuseppe; Caprini, Mihai; Corso-Radu, Alina; D'ascanio, Matteo; De Castro Vargas Fernandes, Julio; Kazarov, Andrei; Kolobara, Bernard; Lankford, Andrew; Laurent, Florian; Lehmann Miotto, Giovanna; Magnoni, Luca; Papaevgeniou, Lykourgos; Ryabov, Yury; Santos, Alejandro; Seixas, Jose; Soloviev, Igor; Unel, Gokhan; Yasu, Yoshiji

    2016-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider (LHC) at CERN is composed of a large number of distributed hardware and software components which in a coordinated manner provide the data-taking functionality of the overall system. The Controls and Configuration (CC) software offers services to configure, control and monitor the TDAQ system. It is a framework which provides essentially the glue that holds the various sub-systems together. While the overall architecture, established at the end of the 90’s, has proven to be solid and flexible, many software components (from core services, like the Run Control and the error management system, to end- user tools) have undergone a complete redesign or re-implementation during the LHC’s Long Shutdown I period. The upgrades were driven by the need to fold-in the additional requirements that appeared in the course of LHC’s Run 1, to profit from new technologies and to re-factorize and cleanup the code. This paper...

  5. Editor for Remote Database used in ATLAS Trigger/DAQ

    CERN Document Server

    Meessen, C; Valenta, J

    2006-01-01

    The poster gives brief summary of the ATLAS T/DAQ system, then it introduces the RDB database and describes the RDB Editor application, including its internal structure, GUI features, etc. The RDB Editor is an easy-to-use Java application which allows simple navigation between huge number of objects stored in the RDB. It supports bookmarks, histories, etc. in the way usual in the web browsers. Moreover, it is possible to enhance the application by specialized (graphical) viewers for objects of particular class which will allow the user to see, for example, details that are hard to spot in textual view. As an example of such a plug-in, viewer for EFD_Configuration class was developed.

  6. Upgrade and integration of the configuration and monitoring tools for the ATLAS Online farm

    CERN Document Server

    Ballestrero, S; The ATLAS collaboration; Darlea, G L; Dumitru, I; Scannicchio, DA; Twomey, M S; Valsan, M L; Zaytsev, A

    2012-01-01

    The ATLAS Online farm is a non-homogeneous cluster of nearly 3000 PCs which run the data acquisition, trigger and control of the ATLAS detector. The systems are configured and monitored by a combination of open-source tools, such as Quattor and Nagios, and tools developed in-house, such as ConfDB. We report on the ongoing introduction of new provisioning and configuration tools, Puppet and ConfDB v2 which are more flexible and allow automation for previously uncovered needs, and on the upgrade and integration of the monitoring and alerting tools, including the interfacing of these with the TDAQ Shifter Assistant software and their integration with configuration tools. We discuss the selection of the tools and the assessment of their functionality and performance, and how they enabled the introduction of virtualization for selected services.

  7. Upgrade and integration of the configuration and monitoring tools for the ATLAS Online farm

    International Nuclear Information System (INIS)

    Ballestrero, S; Darlea, G–L; Twomey, M S; Brasolin, F; Dumitru, I; Valsan, M L; Scannicchio, D A; Zaytsev, A

    2012-01-01

    The ATLAS Online farm is a non-homogeneous cluster of nearly 3000 systems which run the data acquisition, trigger and control of the ATLAS detector. The systems are configured and monitored by a combination of open-source tools, such as Quattor and Nagios, and tools developed in-house, such as ConfDB. We report on the ongoing introduction of new provisioning and configuration tools, Puppet and ConfDB v2, which are more flexible and allow automation for previously uncovered needs, and on the upgrade and integration of the monitoring and alerting tools, including the interfacing of these with the TDAQ Shifter Assistant software and their integration with configuration tools. We discuss the selection of the tools and the assessment of their functionality and performance, and how they enabled the introduction of virtualization for selected services.

  8. Test Beam Coordination: 2003 ATLAS Combined Test Beam

    CERN Multimedia

    Di Girolamo, B.

    The 2003 Test Beam Period The 2003 Test Beam period has been very fruitful for ATLAS. In spite of several days lost because of the accelerator problems, ATLAS has been able to achieve many results: FCAL has completed the calibration program in H6 Tilecal has completed the calibration program in H8 Pixel has performed extensive studies with normal and high intensity beams (up to 1.4*108 hadrons/spill) SCT has completed a variety of studies with quite a high number of modules operated concurrently TRT has performed several studies at high, low and very low energy (first use of the new H8 beam in the range 1 to 9 GeV) Muons (MDT,RPC and TGC) have been operating a large setup for about 5 months. The almost final MDT ROD (MROD) has been integrated in the readout and the final trigger electronics for TGC and RPC has been tested and certified with normal beam and during dedicated 40 MHz beam periods. The TDAQ has exploited a new generation prototype successfully and the new Event Filter infrastructure f...

  9. Development and Tests of the Event Filter for the ATLAS Experiment

    CERN Document Server

    Bosman, M; Negri, A; Segura, E; Sushkov, S; Touchard, F; Wheeler, S J; 14th IEEE - NPSS Real Time Conference 2005 Nuclear Plasma Sciences Society

    2005-01-01

    The Trigger and Data Acquisition (TDAQ) System of the ATLAS Experiment comprises three stages of event selection. The Event Filter (EF) is the third level trigger and is software implemented. Its primary goal is the final selection of interesting events with reduction of the event rate down to ~200 Hz acceptable by the mass storage. The EF System will be implemented as a set of independent commodity components Sub-Farms, each connected to the Event Builder subsystem to receive full events and on the other side to the Sub-Farm Output nodes, where the selected events are forwarded to mass storage. A distinctive feature of the Event Filter is its ability to use the full event data for selection directly based on the offline reconstruction and analysis algorithms. Besides the main duties on event triggering and data transportation, the EF is also able to provide additional functionalities, like monitoring of the selected events and online calibration of the ATLAS detectors. Significant design improvements are cur...

  10. Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

    Science.gov (United States)

    Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

    2017-12-01

    State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with

  11. The Evolution of the Region of Interest Builder in the ATLAS Experiment at CERN

    CERN Document Server

    Rifki, Othmane; The ATLAS collaboration; Crone, Gordon Jeremy; Green, Barry; Love, Jeremy; Proudfoot, James; Panduro Vazquez, William; Vandelli, Wainer; Zhang, Jinlong

    2015-01-01

    ATLAS is a general purpose particle detector at the Large Hadron Collider (LHC) at CERN designed to measure the products of proton collisions. Given their high interaction rate (1GHz), selective triggering in real time is required to reduce the rate to the experiment’s data storage capacity (1KHz). To meet this requirement, ATLAS employs a combination of hardware and software triggers to select interesting collisions for physics analysis. The Region of Interest Builder (RoIB) is an integral part of the ATLAS detector Trigger and Data Acquisition (TDAQ) chain where the coordinates of the regions of interest (RoIs) identified by the first level trigger (L1) are collected and passed to the High Level Trigger (HLT) to make a decision. While the current custom RoIB operated reliably during the first run of the LHC, it is desirable to have the RoIB more operationally maintainable in the new run, which will reach higher luminosities with an increased complexity of L1 triggers. We are responsible for migrating the ...

  12. The readiness of ATLAS Trigger-DAQ system for the second LHC run

    CERN Document Server

    Rammensee, Michael; The ATLAS collaboration

    2015-01-01

    After its first shutdown, LHC will provide pp collisions with increased luminosity and energy. In the ATLAS experiment, the Trigger and Data Acquisition (TDAQ) system has been upgraded to deal with the increased event rates. The updated system is radically different from the previous implementation, both in terms of architecture and expected performance. The main architecture has been reshaped in order to profit from the technological progress and to maximize the flexibility and efficiency of the data selection process. The trigger system in ATLAS consists of a hardware Level-1 (L1) and a software based high-level trigger (HLT) that reduces the event rate from the design bunch-crossing rate of 40 MHz to an average recording rate of a few hundred Hz. The pre-existing two-level software filtering, known as L2 and the Event Filter, are now merged into a single process, performing incremental data collection and analysis. This design has many advantages, among which are: the radical simplification of the architec...

  13. The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

    CERN Document Server

    Kazarov, A; The ATLAS collaboration; Magnoni, L

    2011-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for filtering and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The huge flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This require strong competence and experience in understanding and discovering problems and root causes, and often the meaningful in...

  14. The AAL project: Automated monitoring and intelligent AnaLysis for the ATLAS data taking infrastructure

    CERN Document Server

    Magnoni, L; The ATLAS collaboration; Kazarov, A

    2011-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for filtering and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The huge flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This require strong competence and experience in understanding and discovering problems and root causes, and often the meaningful in...

  15. An SDN based approach for the ATLAS data acquisition network

    CERN Document Server

    Blikra, Espen; The ATLAS collaboration

    2016-01-01

    ATLAS is a high energy physics experiment in the Large Hadron Collider located at CERN. During the so called Long Shutdown 2 period scheduled for late 2019, ATLAS will undergo several modifications and upgrades on its data acquisition system in order to cope with the higher luminosity requirements. As part of these activities, a new read-out chain will be built for the New Small Wheel muon detector and the one of the Liquid Argon calorimeter will be upgraded. The subdetector specific electronic boards will be replaced with new commodity-server-based systems and instead of the custom serial-link-based communication, the new system will make use of a yet to be chosen commercial network technology. The new network will be used as a data acquisition network and at the same time it is intended to allow communication for the control, calibration and monitoring of the subdetectors. Therefore several types of traffic with different bandwidth requirements and different criticality will be competing for the same underl...

  16. ATLAS WORLD-cloud and networking in PanDA

    Science.gov (United States)

    Barreiro Megino, F.; De, K.; Di Girolamo, A.; Maeno, T.; Walker, R.; ATLAS Collaboration

    2017-10-01

    The ATLAS computing model was originally designed as static clouds (usually national or geographical groupings of sites) around the Tier 1 centres, which confined tasks and most of the data traffic. Since those early days, the sites’ network bandwidth has increased at 0(1000) and the difference in functionalities between Tier 1s and Tier 2s has reduced. After years of manual, intermediate solutions, we have now ramped up to full usage of World-cloud, the latest step in the PanDA Workload Management System to increase resource utilization on the ATLAS Grid, for all workflows (MC production, data (re)processing, etc.). We have based the development on two new site concepts. Nuclei sites are the Tier 1s and large Tier 2s, where tasks will be assigned and the output aggregated, and satellites are the sites that will execute the jobs and send the output to their nucleus. PanDA dynamically pairs nuclei and satellite sites for each task based on the input data availability, capability matching, site load and network connectivity. This contribution will introduce the conceptual changes for World-cloud, the development necessary in PanDA, an insight into the network model and the first half-year of operational experience.

  17. The atlas network: a “strategic ally” of the tobacco industry

    Science.gov (United States)

    Thompson, Sheryl; Lee, Kelley

    2016-01-01

    Summary Amid growing academic and policy interest in the influence of think tanks in public policy processes, this article demonstrates the extent of tobacco industry partnerships with think tanks in the USA, and analyzes how collaborating with a network of think tanks facilitated tobacco industry influence in public health policy. Through analysis of documents from tobacco companies and think tanks, we demonstrate that the Atlas Economic Research Foundation, a network of 449 free market think tanks, acted as a strategic ally to the tobacco industry throughout the 1990s. Atlas headquarters, while receiving donations from the industry, also channeled funding from tobacco corporations to think tank actors to produce publications supportive of industry positions. Thirty‐seven per cent of Atlas partner think tanks in the USA received funding from the tobacco industry; the majority of which were also listed as collaborators on public relations strategies or as allies in countering tobacco control efforts. By funding multiple think tanks, within a shared network, the industry was able to generate a conversation among independent policy experts, which reflected its position in tobacco control debates. This demonstrates a coherent strategy by the tobacco industry to work with Atlas to influence public health policies from multiple directions. There is a need for critical analysis of the influence of think tanks in tobacco control and other health policy sectors, as well as greater transparency of their funding and other links to vested interests. © 2016 The Authors The International Journal of Health Planning and Management Published by John Wiley & Sons Ltd PMID:27125556

  18. ATLAS WORLD-cloud and networking in PanDA

    CERN Document Server

    AUTHOR|(SzGeCERN)643806; The ATLAS collaboration; De, Kaushik; Di Girolamo, Alessandro; Maeno, Tadashi; Walker, Rodney

    2017-01-01

    The ATLAS computing model was originally designed as static clouds (usually national or geographical groupings of sites) around the Tier 1 centres, which confined tasks and most of the data traffic. Since those early days, the sites' network bandwidth has increased at 0(1000) and the difference in functionalities between Tier 1s and Tier 2s has reduced. After years of manual, intermediate solutions, we have now ramped up to full usage of World-cloud, the latest step in the PanDA Workload Management System to increase resource utilization on the ATLAS Grid, for all workflows (MC production, data (re)processing, etc.). We have based the development on two new site concepts. Nuclei sites are the Tier 1s and large Tier 2s, where tasks will be assigned and the output aggregated, and satellites are the sites that will execute the jobs and send the output to their nucleus. PanDA dynamically pairs nuclei and satellite sites for each task based on the input data availability, capability matching, site load and network...

  19. A neural network clustering algorithm for the ATLAS silicon pixel detector

    CERN Document Server

    Aad, Georges; Abdallah, Jalal; Abdel Khalek, Samah; Abdinov, Ovsat; Aben, Rosemarie; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Adelman, Jahred; Adomeit, Stefanie; Adye, Tim; Agatonovic-Jovin, Tatjana; Aguilar-Saavedra, Juan Antonio; Agustoni, Marco; Ahlen, Steven; Ahmadov, Faig; Aielli, Giulio; Akerstedt, Henrik; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Alberghi, Gian Luigi; Albert, Justin; Albrand, Solveig; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Alimonti, Gianluca; Alio, Lion; Alison, John; Allbrooke, Benedict; Allison, Lee John; Allport, Phillip; Almond, John; Aloisio, Alberto; Alonso, Alejandro; Alonso, Francisco; Alpigiani, Cristiano; Altheimer, Andrew David; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral Coutinho, Yara; Amelung, Christoph; Amidei, Dante; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amram, Nir; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Anduaga, Xabier; Angelidakis, Stylianos; Angelozzi, Ivan; Anger, Philipp; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Araque, Juan Pedro; Arce, Ayana; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnal, Vanessa; Arnold, Hannah; Arratia, Miguel; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Asai, Shoji; Asbah, Nedaa; Ashkenazi, Adi; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Auerbach, Benjamin; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baas, Alessandra; Bacci, Cesare; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Backus Mayes, John; Badescu, Elisabeta; Bagiacchi, Paolo; Bagnaia, Paolo; Bai, Yu; Bain, Travis; Baines, John; Baker, Oliver Keith; Balek, Petr; Balli, Fabrice; Banas, Elzbieta; Banerjee, Swagato; Bannoura, Arwa A E; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Barnovska, Zuzana; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Bartsch, Valeria; Bassalat, Ahmed; Basye, Austin; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Marco; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Anne Kathrin; Becker, Sebastian; Beckingham, Matthew; Becot, Cyril; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Beemster, Lars; Beermann, Thomas; Begel, Michael; Behr, Katharina; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belotskiy, Konstantin; Beltramello, Olga; Benary, Odette; Benchekroun, Driss; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Beringer, Jürg; Bernard, Clare; Bernat, Pauline; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertoli, Gabriele; Bertolucci, Federico; Bertsche, David; Besana, Maria Ilaria; Besjes, Geert-Jan; Bessidskaia, Olga; Bessner, Martin Florian; Besson, Nathalie; Betancourt, Christopher; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianchini, Louis; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilbao De Mendizabal, Javier; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Black, Curtis; Black, James; Black, Kevin; Blackburn, Daniel; Blair, Robert; Blanchard, Jean-Baptiste; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Bock, Christopher; Boddy, Christopher Richard; Boehler, Michael; Boek, Thorsten Tobias; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Bohm, Jan; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Boldyrev, Alexey; Bomben, Marco; Bona, Marcella; Boonekamp, Maarten; Borisov, Anatoly; Borissov, Guennadi; Borri, Marcello; Borroni, Sara; Bortfeldt, Jonathan; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Boterenbrood, Hendrik; Boudreau, Joseph; Bouffard, Julian; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Bousson, Nicolas; Boutouil, Sara; Boveia, Antonio; Boyd, James; Boyko, Igor; Bracinik, Juraj; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Brazzale, Simone Federico; Brelier, Bertrand; Brendlinger, Kurt; Brennan, Amelia Jean; Brenner, Richard; Bressler, Shikma; Bristow, Kieran; Bristow, Timothy Michael; Britton, Dave; Brochu, Frederic; Brock, Ian; Brock, Raymond; Bromberg, Carl; Bronner, Johanna; Brooijmans, Gustaaf; Brooks, Timothy; Brooks, William; Brosamer, Jacquelyn; Brost, Elizabeth; Brown, Jonathan; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Buehrer, Felix; Bugge, Lars; Bugge, Magnar Kopangen; Bulekov, Oleg; Bundock, Aaron Colin; Burckhart, Helfried; Burdin, Sergey; Burghgrave, Blake; Burke, Stephen; Burmeister, Ingo; Busato, Emmanuel; Büscher, Daniel; Büscher, Volker; Bussey, Peter; Buszello, Claus-Peter; Butler, Bart; Butler, John; Butt, Aatif Imtiaz; Buttar, Craig; Butterworth, Jonathan; Butti, Pierfrancesco; Buttinger, William; Buzatu, Adrian; Byszewski, Marcin; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calandri, Alessandro; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Camarda, Stefano; Cameron, David; Caminada, Lea Michaela; Caminal Armadans, Roger; Campana, Simone; Campanelli, Mario; Campoverde, Angel; Canale, Vincenzo; Canepa, Anadi; Cano Bret, Marc; Cantero, Josu; Cantrill, Robert; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capua, Marcella; Caputo, Regina; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Sascha; Carquin, Edson; Carrillo-Montoya, German D; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Casolino, Mirkoantonio; Castaneda-Miranda, Elizabeth; Castelli, Angelantonio; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Catastini, Pierluigi; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cavaliere, Viviana; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerio, Benjamin; Cerny, Karel; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cerv, Matevz; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chalupkova, Ina; Chang, Philip; Chapleau, Bertrand; Chapman, John Derek; Charfeddine, Driss; Charlton, Dave; Chau, Chav Chhiv; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chegwidden, Andrew; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Karen; Chen, Liming; Chen, Shenjian; Chen, Xin; Chen, Yujiao; Cheng, Hok Chuen; Cheng, Yangyang; Cheplakov, Alexander; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Chevalier, Laurent; Chiarella, Vitaliano; Chiefari, Giovanni; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chislett, Rebecca Thalatta; Chitan, Adrian; Chizhov, Mihail; Chouridou, Sofia; Chow, Bonnie Kar Bo; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Chwastowski, Janusz; Chytka, Ladislav; Ciapetti, Guido; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciocio, Alessandra; Cirkovic, Predrag; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Clarke, Robert; Cleland, Bill; Clemens, Jean-Claude; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coffey, Laurel; Cogan, Joshua Godfrey; Coggeshall, James; Cole, Brian; Cole, Stephen; Colijn, Auke-Pieter; Collot, Johann; Colombo, Tommaso; Colon, German; Compostella, Gabriele; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Connell, Simon Henry; Connelly, Ian; Consonni, Sofia Maria; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cooper-Smith, Neil; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Corso-Radu, Alina; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Côté, David; Cottin, Giovanna; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Cree, Graham; Crépé-Renaudin, Sabine; Crescioli, Francesco; Cribbs, Wayne Allen; Crispin Ortuzar, Mireia; Cristinziani, Markus; Croft, Vince; Crosetti, Giovanni; Cuciuc, Constantin-Mihai; Cuhadar Donszelmann, Tulay; Cummings, Jane; Curatolo, Maria; Cuthbert, Cameron; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dafinca, Alexandru; Dai, Tiesheng; Dale, Orjan; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Daniells, Andrew Christopher; Dano Hoffmann, Maria; Dao, Valerio; Darbo, Giovanni; Darmora, Smita; Dassoulas, James; Dattagupta, Aparajita; Davey, Will; David, Claire; Davidek, Tomas; Davies, Eleanor; Davies, Merlin; Davignon, Olivier; Davison, Adam; Davison, Peter; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Daya-Ishmukhametova, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Cecco, Sandro; De Groot, Nicolo; de Jong, Paul; De la Torre, Hector; De Lorenzi, Francesco; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dechenaux, Benjamin; Dedovich, Dmitri; Deigaard, Ingrid; Del Peso, Jose; Del Prete, Tarcisio; Deliot, Frederic; Delitzsch, Chris Malena; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Dell'Orso, Mauro; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deterre, Cecile; Deviveiros, Pier-Olivier; Dewhurst, Alastair; Dhaliwal, Saminder; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Domenico, Antonio; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Di Valentino, David; Dias, Flavia; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dimitrievska, Aleksandra; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Barros do Vale, Maria Aline; Do Valle Wemans, André; Doan, Thi Kieu Oanh; Dobos, Daniel; Doglioni, Caterina; Doherty, Tom; Dohmae, Takeshi; Dolejsi, Jiri; Dolezal, Zdenek; Dolgoshein, Boris; Donadelli, Marisilvia; Donati, Simone; Dondero, Paolo; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dova, Maria-Teresa; Doyle, Tony; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Dubreuil, Emmanuelle; Duchovni, Ehud; Duckeck, Guenter; Ducu, Otilia Anamaria; Duda, Dominik; Dudarev, Alexey; Dudziak, Fanny; Duflot, Laurent; Duguid, Liam; Dührssen, Michael; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Durglishvili, Archil; Dwuznik, Michal; Dyndal, Mateusz; Ebke, Johannes; Edson, William; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Endo, Masaki; Engelmann, Roderich; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernis, Gunar; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Esch, Hendrik; Escobar, Carlos; Esposito, Bellisario; Etienvre, Anne-Isabelle; Etzion, Erez; Evans, Hal; Ezhilov, Alexey; Fabbri, Laura; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Falla, Rebecca Jane; Faltova, Jana; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Favareto, Andrea; Fayard, Louis; Federic, Pavol; Fedin, Oleg; Fedorko, Wojciech; Fehling-Kaschek, Mirjam; Feigl, Simon; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenyuk, Alexander; Fernandez Perez, Sonia; Ferrag, Samir; Ferrando, James; Ferrari, Arnaud; Ferrari, Pamela; 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Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gadatsch, Stefan; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Galster, Gorm Aske Gram Krohn; Gan, KK; Gandrajula, Reddy Pratap; Gao, Jun; Gao, Yongsheng; Garay Walls, Francisca; Garberson, Ford; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gauzzi, Paolo; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Ge, Peng; Gecse, Zoltan; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; George, Matthias; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghazlane, Hamid; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giangiobbe, Vincent; Giannetti, Paola; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Stephen; Gilchriese, Murdock; Gillam, Thomas; Gillberg, Dag; Gilles, Geoffrey; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Filippo Maria; Giorgi, Francesco Michelangelo; Giraud, Pierre-Francois; Giugni, Danilo; Giuliani, Claudia; Giulini, Maddalena; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glaysher, Paul; Glazov, Alexandre; Glonti, George; Goblirsch-Kolb, Maximilian; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goeringer, Christian; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabas, Herve Marie Xavier; Graber, Lars; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Gray, Heather; Graziani, Enrico; Grebenyuk, Oleg; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grohs, Johannes Philipp; Grohsjean, Alexander; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Groth-Jensen, Jacob; Grout, Zara Jane; Guan, Liang; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guicheney, Christophe; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Gunther, Jaroslav; Guo, Jun; Gupta, Shaun; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guttman, Nir; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haber, Carl; Hadavand, Haleh Khani; Haddad, Nacim; Haefner, Petra; Hageböck, Stephan; Hajduk, Zbigniew; Hakobyan, Hrachya; Haleem, Mahsana; Hall, David; Halladjian, Garabed; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Hamnett, Phillip George; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Hanke, Paul; Hanna, Remie; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Hariri, Faten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Paul Fraser; Hartjes, Fred; Hasegawa, Satoshi; Hasegawa, Yoji; Hasib, A; Hassani, Samira; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hayashi, Takayasu; Hayden, Daniel; Hays, Chris; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Lukas; Hejbal, Jiri; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, James; Henderson, Robert; Heng, Yang; Hengler, Christopher; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Hensel, Carsten; Herbert, Geoffrey Henry; Hernández Jiménez, Yesenia; Herrberg-Schubert, Ruth; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hickling, Robert; Higón-Rodriguez, Emilio; Hill, Ewan; Hill, John; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hofmann, Julia Isabell; Hohlfeld, Marc; Holmes, Tova Ray; Hong, Tae Min; Hooft van Huysduynen, Loek; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howard, Jacob; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hsu, Catherine; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Xueye; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Hülsing, Tobias Alexander; Hurwitz, Martina; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Ideal, Emma; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikematsu, Katsumasa; Ikeno, Masahiro; Ilchenko, Iurii; Iliadis, Dimitrios; Ilic, Nikolina; Inamaru, Yuki; Ince, Tayfun; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Iturbe Ponce, Julia Mariana; Iuppa, Roberto; Ivarsson, Jenny; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, Matthew; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jakubek, Jan; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansen, Hendrik; Janssen, Jens; Janus, Michel; Jarlskog, Göran; Javadov, Namig; Javůrek, Tomáš; Jeanty, Laura; Jejelava, Juansher; Jeng, Geng-yuan; Jennens, David; Jenni, Peter; Jentzsch, Jennifer; Jeske, Carl; Jézéquel, Stéphane; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Joergensen, Morten Dam; Johansson, Erik; Johansson, Per; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tim; Jongmanns, Jan; Jorge, Pedro; Joshi, Kiran Daniel; Jovicevic, Jelena; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Jussel, Patrick; Juste Rozas, Aurelio; Kaci, Mohammed; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kajomovitz, Enrique; Kalderon, Charles William; Kama, Sami; Kamenshchikov, Andrey; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karastathis, Nikolaos; Karnevskiy, Mikhail; Karpov, Sergey; Karpova, Zoya; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Katre, Akshay; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazama, Shingo; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Kehoe, Robert; Keil, Markus; Keller, John; Kempster, Jacob Julian; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Khodinov, Alexander; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hee Yeun; Kim, Hyeon Jin; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kiss, Florian; Kittelmann, Thomas; Kiuchi, Kenji; Kladiva, Eduard; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klioutchnikova, Tatiana; Klok, Peter; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohlmann, Simon; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kolanoski, Hermann; Koletsou, Iro; Koll, James; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kondrashova, Nataliia; Köneke, Karsten; König, Adriaan; König, Sebastian; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitriy; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, Jana; Kravchenko, Anton; Kreiss, Sven; Kretz, Moritz; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruse, Amanda; Kruse, Mark; Kruskal, Michael; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Andrew; Kuhl, Thorsten; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurochkin, Yurii; Kurumida, Rie; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; La Rosa, Alessandro; La Rotonda, Laura; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laier, Heiko; Lambourne, Luke; Lammers, Sabine; Lampen, Caleb; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lang, Valerie Susanne; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Lassnig, Mario; Laurelli, Paolo; Lavrijsen, Wim; Law, Alexander; Laycock, Paul; Le, Bao Tran; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Menedeu, Eve; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Claire Alexandra; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leight, William Axel; Leisos, Antonios; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzen, Georg; Lenzi, Bruno; Leone, Robert; Leone, Sandra; Leonhardt, Kathrin; Leonidopoulos, Christos; Leontsinis, Stefanos; Leroy, Claude; Lester, Christopher; Lester, Christopher Michael; Levchenko, Mikhail; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levy, Mark; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Bo; Li, Haifeng; Li, Ho Ling; Li, Lei; Li, Liang; Li, Shu; Li, Yichen; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limbach, Christian; Limosani, Antonio; Lin, Simon; Lin, Tai-Hua; Linde, Frank; Lindquist, Brian Edward; Linnemann, James; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Dong; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Lombardo, Vincenzo Paolo; Long, Brian Alexander; Long, Jonathan; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lopez Paredes, Brais; Lopez Paz, Ivan; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Olof; Lund-Jensen, Bengt; Lungwitz, Matthias; Lynn, David; Lysak, Roman; Lytken, Else; Ma, Hong; Ma, Lian Liang; Maccarrone, Giovanni; Macchiolo, Anna; Machado Miguens, Joana; Macina, Daniela; Madaffari, Daniele; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeno, Mayuko; Maeno, Tadashi; Magradze, Erekle; Mahboubi, Kambiz; Mahlstedt, Joern; Mahmoud, Sara; Maiani, Camilla; Maidantchik, Carmen; Maier, Andreas Alexander; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mamuzic, Judita; Mandelli, Beatrice; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Manfredini, Alessandro; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany Andreina; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Mantifel, Rodger; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchiori, Giovanni; Marcisovsky, Michal; Marino, Christopher; Marjanovic, Marija; Marques, Carlos; Marroquim, Fernando; Marsden, Stephen Philip; Marshall, Zach; Marti, Lukas Fritz; Marti-Garcia, Salvador; Martin, Brian; Martin, Brian Thomas; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Homero; Martinez, Mario; Martin-Haugh, Stewart; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mättig, Peter; Mattmann, Johannes; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazzaferro, Luca; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; Mchedlidze, Gvantsa; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Medinnis, Michael; Meehan, Samuel; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Meloni, Federico; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mercurio, Kevin Michael; Mergelmeyer, Sebastian; Meric, Nicolas; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Milic, Adriana; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Mitsui, Shingo; Miucci, Antonio; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mochizuki, Kazuya; Mohapatra, Soumya; Mohr, Wolfgang; Molander, Simon; Moles-Valls, Regina; Mönig, Klaus; Monini, Caterina; Monk, James; Monnier, Emmanuel; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Moraes, Arthur; Morange, Nicolas; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Motohashi, Kazuki; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Klemens; Mueller, Thibaut; Mueller, Timo; Muenstermann, Daniel; Munwes, Yonathan; Murillo Quijada, Javier Alberto; Murray, Bill; Musheghyan, Haykuhi; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nackenhorst, Olaf; Nadal, Jordi; Nagai, Koichi; Nagai, Ryo; Nagai, Yoshikazu; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Nanava, Gizo; Narayan, Rohin; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Nef, Pascal Daniel; Negri, Andrea; Negri, Guido; Negrini, Matteo; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen, Duong Hai; Nickerson, Richard; Nicolaidou, Rosy; Nicquevert, Bertrand; Nielsen, Jason; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Norberg, Scarlet; Nordberg, Markus; Novgorodova, Olga; Nowak, Sebastian; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; Nuti, Francesco; O'Brien, Brendan Joseph; O'grady, Fionnbarr; O'Neil, Dugan; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Obermann, Theresa; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohman, Henrik; Ohshima, Takayoshi; Okamura, Wataru; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagáčová, Martina; Pagan Griso, Simone; Paganis, Efstathios; Pahl, Christoph; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Palestini, Sandro; Palka, Marek; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panduro Vazquez, William; Pani, Priscilla; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Paolozzi, Lorenzo; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Parker, Michael Andrew; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pasqualucci, Enrico; Passaggio, Stefano; Passeri, Antonio; Pastore, Fernanda; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pearce, James; Pedersen, Maiken; Pedraza Lopez, Sebastian; Pedro, Rute; Peleganchuk, Sergey; Pelikan, Daniel; Peng, Haiping; Penning, Bjoern; Penwell, John; Perepelitsa, Dennis; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perez Reale, Valeria; Perini, Laura; Pernegger, Heinz; Perrino, Roberto; Peschke, Richard; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Pettersson, Nora Emilia; Pezoa, Raquel; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Piccinini, Maurizio; Piegaia, Ricardo; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pina, João Antonio; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Pingel, Almut; Pinto, Belmiro; Pires, Sylvestre; Pitt, Michael; Pizio, Caterina; Plazak, Lukas; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Plucinski, Pawel; Poddar, Sahill; Podlyski, Fabrice; Poettgen, Ruth; Poggioli, Luc; Pohl, David-leon; Pohl, Martin; Polesello, Giacomo; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Pollard, Christopher Samuel; Polychronakos, Venetios; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Poppleton, Alan; Portell Bueso, Xavier; Pospisil, Stanislav; Potamianos, Karolos; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Price, Darren; Price, Joe; Price, Lawrence; Prieur, Damien; Primavera, Margherita; Proissl, Manuel; Prokofiev, Kirill; Prokoshin, Fedor; Protopapadaki, Eftychia-sofia; Protopopescu, Serban; Proudfoot, James; Przybycien, Mariusz; Przysiezniak, Helenka; Ptacek, Elizabeth; Puddu, Daniele; Pueschel, Elisa; Puldon, David; Purohit, Milind; Puzo, Patrick; Qian, Jianming; Qin, Gang; Qin, Yang; Quadt, Arnulf; Quarrie, David; Quayle, William; Queitsch-Maitland, Michaela; Quilty, Donnchadha; Qureshi, Anum; Radeka, Veljko; Radescu, Voica; Radhakrishnan, Sooraj Krishnan; Radloff, Peter; Rados, Pere; Ragusa, Francesco; Rahal, Ghita; Rajagopalan, Srinivasan; Rammensee, Michael; Randle-Conde, Aidan Sean; Rangel-Smith, Camila; Rao, Kanury; Rauscher, Felix; Rave, Tobias Christian; Ravenscroft, Thomas; Raymond, Michel; Read, Alexander Lincoln; Readioff, Nathan Peter; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Rehnisch, Laura; Reisin, Hernan; Relich, Matthew; Rembser, Christoph; Ren, Huan; Ren, Zhongliang; Renaud, Adrien; Rescigno, Marco; Resconi, Silvia; Rezanova, Olga; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Ridel, Melissa; Rieck, Patrick; Rieger, Julia; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Ritsch, Elmar; Riu, Imma; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Roda, Chiara; Rodrigues, Luis; Roe, Shaun; Røhne, Ole; Rolli, Simona; Romaniouk, Anatoli; Romano, Marino; Romero Adam, Elena; Rompotis, Nikolaos; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Matthew; Rosendahl, Peter Lundgaard; Rosenthal, Oliver; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rosten, Rachel; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexandre; Rozen, Yoram; Ruan, Xifeng; Rubbo, Francesco; Rubinskiy, Igor; Rud, Viacheslav; Rudolph, Christian; Rudolph, Matthew Scott; Rühr, Frederik; Ruiz-Martinez, Aranzazu; Rurikova, Zuzana; Rusakovich, Nikolai; Ruschke, Alexander; Rutherfoord, John; Ruthmann, Nils; Ryabov, Yury; Rybar, Martin; Rybkin, Grigori; Ryder, Nick; Saavedra, Aldo; Sacerdoti, Sabrina; Saddique, Asif; Sadeh, Iftach; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Sakamoto, Hiroshi; Sakurai, Yuki; Salamanna, Giuseppe; Salamon, Andrea; Saleem, Muhammad; Salek, David; Sales De Bruin, Pedro Henrique; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvachua Ferrando, Belén; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Sanchez, Arturo; Sánchez, Javier; Sanchez Martinez, Victoria; Sandaker, Heidi; Sandbach, Ruth Laura; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sankey, Dave; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapp, Kevin; Sapronov, Andrey; Saraiva, João; Sarrazin, Bjorn; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Yuichi; Sauvage, Gilles; Sauvan, Emmanuel; Savard, Pierre; Savu, Dan Octavian; Sawyer, Craig; Sawyer, Lee; Saxon, David; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scanlon, Tim; Scannicchio, Diana; Scarcella, Mark; Scarfone, Valerio; Schaarschmidt, Jana; Schacht, Peter; Schaefer, Douglas; Schaefer, Ralph; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R. Dean; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schiavi, Carlo; Schieck, Jochen; Schillo, Christian; Schioppa, Marco; Schlenker, Stefan; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Christopher; Schmitt, Sebastian; Schneider, Basil; Schnellbach, Yan Jie; Schnoor, Ulrike; Schoeffel, Laurent; Schoening, Andre; Schoenrock, Bradley Daniel; Schorlemmer, Andre Lukas; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schramm, Steven; Schreyer, Manuel; Schroeder, Christian; Schuh, Natascha; Schultens, Martin Johannes; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwanenberger, Christian; Schwartzman, Ariel; Schwegler, Philipp; Schwemling, Philippe; Schwienhorst, Reinhard; Schwindling, Jerome; Schwindt, Thomas; Schwoerer, Maud; Sciacca, Gianfranco; Scifo, Estelle; Sciolla, Gabriella; Scott, Bill; Scuri, Fabrizio; Scutti, Federico; Searcy, Jacob; Sedov, George; Sedykh, Evgeny; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Sekula, Stephen; Selbach, Karoline Elfriede; Seliverstov, Dmitry; Sellers, Graham; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Serre, Thomas; Seuster, Rolf; Severini, Horst; Sfiligoj, Tina; Sforza, Federico; Sfyrla, Anna; Shabalina, Elizaveta; Shamim, Mansoora; Shan, Lianyou; Shang, Ruo-yu; Shank, James; Shapiro, Marjorie; Shatalov, Pavel; Shaw, Kate; Shehu, Ciwake Yusufu; Sherwood, Peter; Shi, Liaoshan; Shimizu, Shima; Shimmin, Chase Owen; Shimojima, Makoto; Shiyakova, Mariya; Shmeleva, Alevtina; Shochet, Mel; Short, Daniel; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Shushkevich, Stanislav; Sicho, Petr; Sidiropoulou, Ourania; Sidorov, Dmitri; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silva, José; Silver, Yiftah; Silverstein, Daniel; Silverstein, Samuel; Simak, Vladislav; Simard, Olivier; Simic, Ljiljana; Simion, Stefan; Simioni, Eduard; Simmons, Brinick; Simoniello, Rosa; Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sisakyan, Alexei; Sivoklokov, Serguei; Sjölin, Jörgen; Sjursen, Therese; Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Smakhtin, Vladimir; Smart, Ben; Smestad, Lillian; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snidero, Giacomo; Snyder, Scott; Sobie, Randall; Socher, Felix; Soffer, Abner; Soh, Dart-yin; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Soloshenko, Alexei; Solovyanov, Oleg; Solovyev, Victor; Sommer, Philip; Song, Hong Ye; Soni, Nitesh; Sood, Alexander; Sopczak, Andre; Sopko, Bruno; Sopko, Vit; Sorin, Veronica; Sosebee, Mark; Soualah, Rachik; Soueid, Paul; Soukharev, Andrey; South, David; Spagnolo, Stefania; Spanò, Francesco; Spearman, William Robert; Spettel, Fabian; Spighi, Roberto; Spigo, Giancarlo; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St Denis, Richard Dante; Staerz, Steffen; Stahlman, Jonathan; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanescu-Bellu, Madalina; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staszewski, Rafal; Stavina, Pavel; Steinberg, Peter; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stern, Sebastian; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoebe, Michael; Stoicea, Gabriel; Stolte, Philipp; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Stramaglia, Maria Elena; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Stroynowski, Ryszard; Stucci, Stefania Antonia; Stugu, Bjarne; Styles, Nicholas Adam; Su, Dong; Su, Jun; Subramania, Halasya Siva; Subramaniam, Rajivalochan; Succurro, Antonella; Sugaya, Yorihito; Suhr, Chad; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Svatos, Michal; Swedish, Stephen; Swiatlowski, Maximilian; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Taccini, Cecilia; Tackmann, Kerstin; Taenzer, Joe; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tam, Jason; Tan, Kong Guan; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanasijczuk, Andres Jorge; Tannenwald, Benjamin Bordy; Tannoury, Nancy; Tapprogge, Stefan; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tavares Delgado, Ademar; Tayalati, Yahya; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teischinger, Florian Alfred; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Teoh, Jia Jian; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thong, Wai Meng; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tiouchichine, Elodie; Tipton, Paul; Tisserant, Sylvain; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tollefson, Kirsten; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Topilin, Nikolai; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Tran, Huong Lan; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Tripiana, Martin; Triplett, Nathan; Trischuk, William; Trocmé, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trovatelli, Monica; True, Patrick; Trzebinski, Maciej; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsirintanis, Nikolaos; Tsiskaridze, Shota; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsuno, Soshi; Tsybychev, Dmitri; Tudorache, Alexandra; Tudorache, Valentina; Tuna, Alexander Naip; Tupputi, Salvatore; Turchikhin, Semen; Turecek, Daniel; Turk Cakir, Ilkay; Turra, Ruggero; Tuts, Michael; Tykhonov, Andrii; Tylmad, Maja; Tyndel, Mike; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ughetto, Michael; Ugland, Maren; Uhlenbrock, Mathias; Ukegawa, Fumihiko; Unal, Guillaume; Undrus, Alexander; Unel, Gokhan; Ungaro, Francesca; Unno, Yoshinobu; Urbaniec, Dustin; Urquijo, Phillip; Usai, Giulio; Usanova, Anna; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Valencic, Nika; Valentinetti, Sara; Valero, Alberto; Valery, Loic; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; Van Den Wollenberg, Wouter; Van Der Deijl, Pieter; van der Geer, Rogier; van der Graaf, Harry; Van Der Leeuw, Robin; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; van Woerden, Marius Cornelis; Vanadia, Marco; Vandelli, Wainer; Vanguri, Rami; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Vardanyan, Gagik; Vari, Riccardo; Varnes, Erich; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vazeille, Francois; Vazquez Schroeder, Tamara; Veatch, Jason; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Venturini, Alessio; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Viazlo, Oleksandr; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Vigne, Ralph; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinogradov, Vladimir; Virzi, Joseph; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vladoiu, Dan; Vlasak, Michal; Vogel, Adrian; Vogel, Marcelo; Vokac, Petr; Volpi, Guido; Volpi, Matteo; von der Schmitt, Hans; von Radziewski, Holger; von Toerne, Eckhard; Vorobel, Vit; Vorobev, Konstantin; Vos, Marcel; Voss, Rudiger; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vu Anh, Tuan; Vuillermet, Raphael; Vukotic, Ilija; Vykydal, Zdenek; Wagner, Peter; Wagner, Wolfgang; Wahlberg, Hernan; Wahrmund, Sebastian; Wakabayashi, Jun; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wall, Richard; Waller, Peter; Walsh, Brian; Wang, Chao; Wang, Chiho; Wang, Fuquan; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Kuhan; Wang, Rui; Wang, Song-Ming; Wang, Tan; Wang, Xiaoxiao; Wanotayaroj, Chaowaroj; Warburton, Andreas; Ward, Patricia; Wardrope, David Robert; Warsinsky, Markus; Washbrook, Andrew; Wasicki, Christoph; Watkins, Peter; Watson, Alan; Watson, Ian; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Ben; Webb, Samuel; Weber, Michele; Weber, Stefan Wolf; Webster, Jordan S; Weidberg, Anthony; Weigell, Philipp; Weinert, Benjamin; Weingarten, Jens; Weiser, Christian; Weits, Hartger; Wells, Phillippa; Wenaus, Torre; Wendland, Dennis; Weng, Zhili; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Matthias; Werner, Per; Wessels, Martin; Wetter, Jeffrey; Whalen, Kathleen; White, Andrew; White, Martin; White, Ryan; White, Sebastian; Whiteson, Daniel; Wicke, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik-Fuchs, Liv Antje Mari; Wijeratne, Peter Alexander; Wildauer, Andreas; Wildt, Martin Andre; Wilkens, Henric George; Will, Jonas Zacharias; Williams, Hugh; Williams, Sarah; Willis, Christopher; Willocq, Stephane; Wilson, Alan; Wilson, John; Wingerter-Seez, Isabelle; Winklmeier, Frank; Winter, Benedict Tobias; Wittgen, Matthias; Wittig, Tobias; Wittkowski, Josephine; Wollstadt, Simon Jakob; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wozniak, Krzysztof; Wright, Michael; Wu, Mengqing; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wyatt, Terry Richard; Wynne, Benjamin; Xella, Stefania; Xiao, Meng; Xu, Da; Xu, Lailin; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamaguchi, Yohei; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamauchi, Katsuya; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Hongtao; Yang, Un-Ki; Yang, Yi; Yanush, Serguei; Yao, Liwen; Yao, Weiming; Yasu, Yoshiji; Yatsenko, Elena; Yau Wong, Kaven Henry; Ye, Jingbo; Ye, Shuwei; Yen, Andy L; Yildirim, Eda; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Rikutaro; Yoshihara, Keisuke; Young, Charles; Young, Christopher John; Youssef, Saul; Yu, David Ren-Hwa; Yu, Jaehoon; Yu, Jiaming; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Yusuff, Imran; Zabinski, Bartlomiej; Zaidan, Remi; Zaitsev, Alexander; Zaman, Aungshuman; Zambito, Stefano; Zanello, Lucia; Zanzi, Daniele; Zeitnitz, Christian; Zeman, Martin; Zemla, Andrzej; Zengel, Keith; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhang, Dongliang; Zhang, Fangzhou; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Lei; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Zhengguo; Zhemchugov, Alexey; Zhong, Jiahang; Zhou, Bing; Zhou, Lei; Zhou, Ning; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhukov, Konstantin; Zibell, Andre; Zieminska, Daria; Zimine, Nikolai; Zimmermann, Christoph; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Zinonos, Zinonas; Ziolkowski, Michael; Zobernig, Georg; Zoccoli, Antonio; zur Nedden, Martin; Zurzolo, Giovanni; Zutshi, Vishnu; Zwalinski, Lukasz

    2014-09-15

    A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.

  20. Hippocampal unified multi-atlas network (HUMAN): protocol and scale validation of a novel segmentation tool.

    Science.gov (United States)

    Amoroso, N; Errico, R; Bruno, S; Chincarini, A; Garuccio, E; Sensi, F; Tangaro, S; Tateo, A; Bellotti, R

    2015-11-21

    In this study we present a novel fully automated Hippocampal Unified Multi-Atlas-Networks (HUMAN) algorithm for the segmentation of the hippocampus in structural magnetic resonance imaging. In multi-atlas approaches atlas selection is of crucial importance for the accuracy of the segmentation. Here we present an optimized method based on the definition of a small peri-hippocampal region to target the atlas learning with linear and non-linear embedded manifolds. All atlases were co-registered to a data driven template resulting in a computationally efficient method that requires only one test registration. The optimal atlases identified were used to train dedicated artificial neural networks whose labels were then propagated and fused to obtain the final segmentation. To quantify data heterogeneity and protocol inherent effects, HUMAN was tested on two independent data sets provided by the Alzheimer's Disease Neuroimaging Initiative and the Open Access Series of Imaging Studies. HUMAN is accurate and achieves state-of-the-art performance (Dice[Formula: see text] and Dice[Formula: see text]). It is also a robust method that remains stable when applied to the whole hippocampus or to sub-regions (patches). HUMAN also compares favorably with a basic multi-atlas approach and a benchmark segmentation tool such as FreeSurfer.

  1. Design of a Hardware Track Finder (Fast Tracker) for the ATLAS Trigger

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00010976; Albicocco, P.; Alison, J.; Ancu, L.S.; Anderson, J.; Andari, N.; Andreani, A.; Andreazza, A.; Annovi, A.; Antonelli, M.; Asbah, N.; Atkinson, M.; Baines, J.; Barberio, E.; Beccherle, R.; Beretta, M.; Bertolucci, F.; Biesuz, N.V.; Blair, R.; Bogdan, M.; Boveia, A.; Britzger, D.; Bryant, P.; Burghgrave, B.; Calderini, G.; Camplani, A.; Cavasinni, V.; Chakraborty, D.; Chang, P.; Cheng, Y.; Citraro, S.; Citterio, M.; Crescioli, F.; Dawe, N.; Dell'Orso, M.; Donati, S.; Dondero, P.; Drake, G.; Gadomski, S.; Gatta, M.; Gentsos, C.; Giannetti, P.; Gkaitatzis, S.; Gramling, J.; Howarth, J.W.; Iizawa, T.; Ilic, N.; Jiang, Z.; Kaji, T.; Kasten, M.; Kawaguchi, Y.; Kim, Y.K.; Kimura, N.; Klimkovich, T.; Kolb, M.; Kordas, K.; Krizka, K.; Kubota, T.; Lanza, A.; Li, H.L.; Liberali, V.; Lisovyi, M.; Liu, L.; Love, J.; Luciano, P.; Luongo, C.; Magalotti, D.; Maznas, I.; Meroni, C.; Mitani, T.; Nasimi, H.; Negri, A.; Neroutsos, P.; Neubauer, M.; Nikolaidis, S.; Okumura, Y.; Pandini, C.; Petridou, C.; Piendibene, M.; Proudfoot, J.; Rados, P.; Roda, C.; Rossi, E.; Sakurai, Y.; Sampsonidis, D.; Saxon, J.; Schmitt, S.; Schoening, A.; Shochet, M.; Shojaii, S.; Soltveit, H.; Sotiropoulou, C.L.; Stabile, A.; Swiatlowski, M.; Tang, F.; Taylor, P.T.; Testa, M.; Tompkins, L.; Vercesi, V.; Volpi, G.; Wang, R.; Watari, R.; Webster, J.; Wu, X.; Yorita, K.; Yurkewicz, A.; Zeng, J.C.; Zhang, J.; Zou, R.

    2016-01-01

    The use of tracking information at the trigger level in the LHC Run II period is crucial for the trigger an data acquisition (TDAQ) system and will be even more so as contemporary collisions that occur at every bunch crossing will increase in Run III. The Fast TracKer (FTK) is part of the ATLAS trigger upgrade project; it is a hardware processor that will provide every Level-1 accepted event (100 kHz) and within 100$\\mu$s, full tracking information for tracks with momentum as low as 1 GeV. Providing fast, extensive access to tracking information, with resolution comparable to the offline reconstruction, FTK will help in precise detection of the primary and secondary vertices to ensure robust selections and improve the trigger performance.

  2. Machine learning of network metrics in ATLAS Distributed Data Management

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00218873; The ATLAS collaboration; Toler, Wesley; Vamosi, Ralf; Bogado Garcia, Joaquin Ignacio

    2017-01-01

    The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our m...

  3. Discrete Event Modeling and Simulation-Driven Engineering for the ATLAS Data Acquisition Network

    CERN Document Server

    Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel

    2016-01-01

    We present an iterative and incremental development methodology for simulation models in network engineering projects. Driven by the DEVS (Discrete Event Systems Specification) formal framework for modeling and simulation we assist network design, test, analysis and optimization processes. A practical application of the methodology is presented for a case study in the ATLAS particle physics detector, the largest scientific experiment built by man where scientists around the globe search for answers about the origins of the universe. The ATLAS data network convey real-time information produced by physics detectors as beams of particles collide. The produced sub-atomic evidences must be filtered and recorded for further offline scrutiny. Due to the criticality of the transported data, networks and applications undergo careful engineering processes with stringent quality of service requirements. A tight project schedule imposes time pressure on design decisions, while rapid technology evolution widens the palett...

  4. Identification of hadronic tau decays at the ATLAS detector using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Duschinger, Dirk; Hanisch, Stefanie; Mader, Wolfgang; Madysa, Nico; Straessner, Arno [Institut fuer Kern- und Teilchenphysik, TU Dresden (Germany)

    2016-07-01

    One of the primary goals of the ATLAS experiment at the LHC is the search for physics beyond the Standard Model. The efficient identification of hadronically decaying tau leptons is crucial for this as they comprise the final states of several decay channels sensitive to new physics. (e. g. Higgs boson decays H → τ{sub had} τ{sub had}) The identification algorithm currently applied at ATLAS utilizes multi-variate methods and reconstructed particle properties to discriminate against QCD jets, which constitute an important background. This talk presents a new neural-network-based approach to hadronic tau decay identification and investigates its dependence on hyperparameters such as the network topology or number of training cycles. Ensembling is presented as a technique to improve classifier performance and robustness against overtraining. The resulting classifier is compared to the current approach based on Boosted Decision Trees. The study is based on 2012 data taken at the ATLAS detector at a center-of-mass energy of √(s)=8 TeV.

  5. Intelligent operations of the data acquisition system of the ATLAS experiment at the LHC

    CERN Document Server

    Anders, G; The ATLAS collaboration; Lehmann Miotto, G; Magnoni, L

    2015-01-01

    The ATLAS experiment at the Large Hadron Collider at CERN relies on a complex and highly distributed Trigger and Data Acquisition (TDAQ) system to gather and select particle collision data obtained at unprecedented energy and rates. The Run Control (RC) system is the component steering the data acquisition by starting and stopping processes and by carrying all data-taking elements through well-defined states in a coherent way. Taking into account all the lessons learnt during LHC’s Run 1, the RC has been completely re-designed and re-implemented during the LHC Long Shutdown 1 (LS1) phase. As a result of the new design, the RC is assisted by the Central Hint and Information Processor (CHIP) service that can be truly considered its “brain”. CHIP is an intelligent system able to supervise the ATLAS data taking, take operational decisions and handle abnormal conditions. In this paper the design, implementation and performances of the RC/CHIP system will be described. A particular emphasis will be put on the...

  6. Machine Learning for ATLAS DDM Network Metrics

    CERN Document Server

    Lassnig, Mario; The ATLAS collaboration; Vamosi, Ralf

    2016-01-01

    The increasing volume of physics data is posing a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from our ongoing automation efforts. First, we describe our framework for distributed data management and network metrics, automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

  7. Implementing a modular framework in a conditions database explorer for ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Simoes, J; Amorim, A; Batista, J; Lopes, L; Neves, R; Pereira, P [SIM and FCUL, University of Lisbon, Campo Grande, P-1749-016 Lisbon (Portugal); Kolos, S [University of California, Irvine, California 92697-4575 (United States); Soloviev, I [Petersburg Nuclear Physics Institute, Gatchina, St-Petersburg RU-188350 (Russian Federation)], E-mail: jalmeida@mail.cern.ch, E-mail: Antonio.Amorim@sim.fc.ul.pt

    2008-07-15

    The ATLAS conditions databases will be used to manage information of quite diverse nature and level of complexity. The usage of a relational database manager like Oracle, together with the object managers POOL and OKS developed in-house, poses special difficulties in browsing the available data while understanding its structure in a general way. This is particularly relevant for the database browser projects where it is difficult to link with the class defining libraries generated by general frameworks such as Athena. A modular approach to tackle these problems is presented here. The database infrastructure is under development using the LCG COOL infrastructure, and provides a powerful information sharing gateway upon many different systems. The nature of the stored information ranges from temporal series of simple values up to very complex objects describing the configuration of systems like ATLAS' TDAQ infrastructure, including also associations to large objects managed outside of the database infrastructure. An important example of this architecture is the Online Objects Extended Database BrowsEr (NODE), which is designed to access and display all data, available in the ATLAS Monitoring Data Archive (MDA), including histograms and data tables. To deal with the special nature of the monitoring objects, a plugin from the MDA framework to the Time managed science Instrument Databases (TIDB2) is used. The database browser is extended, in particular to include operations on histograms such as display, overlap, comparisons as well as commenting and local storage.

  8. Integration of omic networks in a developmental atlas of maize.

    Science.gov (United States)

    Walley, Justin W; Sartor, Ryan C; Shen, Zhouxin; Schmitz, Robert J; Wu, Kevin J; Urich, Mark A; Nery, Joseph R; Smith, Laurie G; Schnable, James C; Ecker, Joseph R; Briggs, Steven P

    2016-08-19

    Coexpression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting functional roles of individual genes at a system-wide scale. To enable network reconstructions, we built a large-scale gene expression atlas composed of 62,547 messenger RNAs (mRNAs), 17,862 nonmodified proteins, and 6227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. Networks in which nodes are genes connected on the basis of highly correlated expression patterns of mRNAs were very different from networks that were based on coexpression of proteins. Roughly 85% of highly interconnected hubs were not conserved in expression between RNA and protein networks. However, networks from either data type were enriched in similar ontological categories and were effective in predicting known regulatory relationships. Integration of mRNA, protein, and phosphoprotein data sets greatly improved the predictive power of GRNs. Copyright © 2016, American Association for the Advancement of Science.

  9. The FTK to Level-2 Interface Card (FLIC)

    CERN Document Server

    Wang, R.; The ATLAS collaboration; Auerbach, Benjamin; Blair, Robert; Drake, Gary; Love, Jeremy; Proudfoot, James; Anderson, J.; Zhang, Jinlong

    2016-01-01

    The FTK to Level-2 Interface Card (FLIC) of the ATLAS Fast TracKer (FTK) trigger upgrade is the final component in the FTK chain of custom electronics. The FTK performs full event tracking using the ATLAS Silicon detectors for every Level-1(L1) accepted event at 100 kHz. The FLIC is a custom Advanced Telecommunications Architecture (ATCA) card that interfaces the upstream FTK system with the ATLAS trigger and data acquisition (TDAQ) system, and allows for event processing on commercial PC blades making use of the 10 GB Ethernet full mesh ATCA back-plane. The FLIC receives data on 8 optical links at a bandwidth of about 1 Gbps per channel, reformats the data to the ATLAS standard record format, and performs the conversion from local to global module identifier using look up tables in SRAM. After processing, the event records are sent out to the TDAQ system using the S-LINK protocol at 2 Gbps, with a latency of O(10 microseconds). The data processing is handled in two Xilinx Virtex-6 FPGAs, with two additional ...

  10. The FTK to Level-2 Interface Card (FLIC)

    CERN Document Server

    Anderson, John Thomas; The ATLAS collaboration; Drake, Gary; Love, Jeremy; Proudfoot, James; Wang, Rui; Zhang, Jinlong; Auerbach, Benjamin

    2015-01-01

    The FTK to Level-2 Interface Card (FLIC) of the ATLAS Fast TracKer (FTK) trigger upgrade is the final component in the FTK chain of custom electronics. The FTK performs full event tracking using the ATLAS Silicon detectors for every Level-1 accepted event at 100 kHz. The FLIC is a custom Advanced Telecommunications Architecture (ATCA) card that interfaces the upstream FTK system with the ATLAS trigger and data acquisition (TDAQ) system, and allows for event processing on commercial PC blades making use of the 10 GB Ethernet full mesh ATCA back-plane. The FLIC receives data on 8 optical links at a bandwidth of ~1 Gbps per channel, reformats the data to the ATLAS standard record format, and performs the conversion from local to global module identifier using look up tables in SRAM. After processing, the event records are sent out to the TDAQ system using the S-LINK protocol at 2 Gbps, with a latency of O(10 microseconds). The data processing is handled in two Xilinx Virtex-6 FPGAs, with two additional Virtex-6 ...

  11. ROS Installation and Commissioning

    CERN Multimedia

    Gorini, B

    The ATLAS Readout group (a sub-group of TDAQ) has now completed the installation and commissioning of all of the Readout System (ROS) units. Event data from ATLAS is initially handled by detector specific hardware and software, but following a Level 1 Accept the data passes from the detector specific Readout Drivers (RODs) to the ROS, the first stage of the central ATLAS DAQ. Within the final ATLAS TDAQ system the ROS stores the data and on request makes it available to the Level 2 Trigger (L2) processors and to the Event Builder (EB) as required. The ROS is implemented as a large number of PCs housing custom built cards (ROBINs) and running custom multi-threaded software. Each ROBIN card (shown below) contains buffer memories to store the data, plus a field programmable gate array ( FPGA ) and an embedded PowerPC processor for management of the memories and data requests, and is implemented as a 64-bit 66 MHz PCI card. Both the software and the ROBIN cards have been designed and developed by the Readout g...

  12. Integrating Network Awareness in ATLAS Distributed Computing Using the ANSE Project

    CERN Document Server

    Klimentov, Alexei; The ATLAS collaboration; Petrosyan, Artem; Batista, Jorge Horacio; Mc Kee, Shawn Patrick

    2015-01-01

    A crucial contributor to the success of the massively scaled global computing system that delivers the analysis needs of the LHC experiments is the networking infrastructure upon which the system is built. The experiments have been able to exploit excellent high-bandwidth networking in adapting their computing models for the most efficient utilization of resources. New advanced networking technologies now becoming available such as software defined networking hold the potential of further leveraging the network to optimize workflows and dataflows, through proactive control of the network fabric on the part of high level applications such as experiment workload management and data management systems. End to end monitoring of networks using perfSONAR combined with data flow performance metrics further allows applications to adapt based on real time conditions. We will describe efforts underway in ATLAS on integrating network awareness at the application level, particularly in workload management, building upon ...

  13. DAL Algorithms and Python

    CERN Document Server

    Aydemir, Bahar

    2017-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider (LHC) at CERN is composed of a large number of distributed hardware and software components. TDAQ system consists of about 3000 computers and more than 25000 applications which, in a coordinated manner, provide the data-taking functionality of the overall system. There is a number of online services required to configure, monitor and control the ATLAS data taking. In particular, the configuration service is used to provide configuration of above components. The configuration of the ATLAS data acquisition system is stored in XML-based object database named OKS. DAL (Data Access Library) allowing to access it's information by C++, Java and Python clients in a distributed environment. Some information has quite complicated structure, so it's extraction requires writing special algorithms. Algorithms available on C++ programming language and partially reimplemented on Java programming language. The goal of the projec...

  14. ATLAS World-cloud and networking in PanDA

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration; De, Kaushik; Di Girolamo, Alessandro; Walker, Rodney

    2016-01-01

    The ATLAS computing model was originally designed as static clouds (usually national or geographical groupings of sites) around the Tier 1 centers, which confined tasks and most of the data traffic. Since those early days, the sites' network bandwidth has increased at O(1000) and the difference in functionalities between Tier 1s and Tier 2s has reduced. After years of manual, intermediate solutions, we have now ramped up to full usage of World-cloud, the latest step in the PanDA Workload Management System to increase resource utilization on the ATLAS Grid, for all workflows (MC production, data (re)processing, etc.). We have based the development on two new site concepts. Nuclei sites are the Tier 1s and large Tier 2s, where tasks will be assigned and the output aggregated, and satellites are the sites that will execute the jobs and send the output to their nucleus. Nuclei and satellite sites are dynamically paired by PanDA for each task based on the input data availability, capability matching, site load and...

  15. Modeling Heterogeneous Carbon Nanotube Networks for Photovoltaic Applications Using Silvaco Atlas Software

    OpenAIRE

    Garfrerick, Adam R.

    2012-01-01

    Recent developments in carbon nanotube technology have allowed for semi-transparent electrodes to be created which can possibly improve the efficiency of solar cells. A method for simulating the use of semi-transparent carbon nanotube networks as a charge collector for solar cells in Silvaco ATLAS software is presented in this thesis. Semi-transparent carbon nanotube networks allow for a greater area of charge collection on the surface of solar cells as well as a lower resistance path for cha...

  16. Test Management Framework for the Data Acquisition of the ATLAS Experiment

    CERN Document Server

    Kazarov, Andrei; The ATLAS collaboration

    2017-01-01

    Data Acquisition (DAQ) of the ATLAS experiment is a large distributed and inhomogeneous system: it consists of thousands of interconnected computers and electronics devices that operate coherently to read out and select relevant physics data. Advanced testing and diagnostics capabilities of the TDAQ control system are a crucial feature which contributes significantly to smooth operation and fast recovery in case of the problems and, finally, to the high efficiency of the whole experiment. The base layer of the verification and diagnostic functionality is a test management framework. We have developed a flexible test management system that allows the experts to define and configure tests for different components, indicate follow-up actions to test failures and describe inter-dependencies between DAQ or detector elements. This development is based on the experience gained with the previous test system that was used during the first three years of the data taking. We discovered that more emphasis needed to be pu...

  17. A revised design and implementation of the ATLAS Log Service package

    Science.gov (United States)

    Murillo Garcia, Raul; Lehamnn Miotto, Giovanna; ATLAS TDAQ Collaboration

    2011-12-01

    This paper presents a revised design and implementation of the Log Service for the ATLAS Trigger and Data Acquisition (TDAQ) framework at CERN. A previous version of this utility was rarely used for various reasons, herein explained. The lessons learned set the grounds and motivation for a new redesign. The Log Service consists of the Logger, the entity that collects logs and stores them in an Oracle database; a set of user utilities to access and maintain the database; and a Java based tool, known as the Log Manager, which provides a compact and intuitive interface for browsing the log messages based on a user defined search criteria. The outline of these software components are explained, including various optimization techniques deployed in order to handle the large volume of entries expected to be stored in the database. Finally, a performance study has been conducted to prove the validity and behavior of the Log Service.

  18. A revised design and implementation of the ATLAS Log Service package

    CERN Document Server

    Murillo García, R; The ATLAS collaboration

    2010-01-01

    This paper presents a revised design and implementation of the Log Service for the ATLAS Trigger and Data Acquisition (TDAQ) framework at CERN. A previous version of this utility was rarely used for various reasons, herein explained. The lessons learned set the grounds and motivation for a new redesign. The Log Service consists of the Logger, the entity that collects logs and stores them in an Oracle database; a set of user utilities to access and maintain the database; and a Java based tool, known as the Log Manager, which provides a compact and intuitive interface for browsing the log messages based on a user defined search criteria. The outline of these software components are explained, including various optimization techniques deployed in order to handle the large volume of entries expected to be stored in the database. Finally, a performance study has been conducted to prove the validity and behavior of the Log Service.

  19. Machine learning of network metrics in ATLAS Distributed Data Management

    Science.gov (United States)

    Lassnig, Mario; Toler, Wesley; Vamosi, Ralf; Bogado, Joaquin; ATLAS Collaboration

    2017-10-01

    The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for networkaware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

  20. Trigger and DAQ in the Combined Test Beam

    CERN Multimedia

    Dobson, M; Padilla, C

    2004-01-01

    Introduction During the Combined Test Beam the latest prototype of the ATLAS Trigger and DAQ system is being used to support the data taking of all the detectors. Further development of the TDAQ subsystems benefits from the direct experience given by the integration in the beam test. Support of detectors for the Combined Test Beam All ATLAS detectors need their own detector-specific DAQ development. The readout electronics is controlled by a Readout Driver (ROD), custom-built for each detector. The ROD receives data for events that are accepted by the first level trigger. The detector-specific part of the DAQ system needs to control the ROD and to respond to commands of the central DAQ (e.g. to "Start" a run). The ROD module then sends event data to a Readout System (ROS), a PC with special receiver modules/buffers. At this point the data enters the realm of the ATLAS DAQ and High Level Trigger system, constructed from Linux PCs connected with gigabit Ethernet networks. Most ATLAS detectors, representing s...

  1. Monitoring the US ATLAS Network Infrastructure with perfSONAR-PS

    CERN Document Server

    McKee, S; The ATLAS collaboration; Laurens, P; Severini, H; Wlodek, T; Wolff, S; Zurawski, J

    2012-01-01

    We will present our motivations for deploying and using the perfSONAR-PS Performance Toolkit at ATLAS sites in the United States and describe our experience in using it. This software creates a dedicated monitoring server, capable of collecting and performing a wide range of passive and active network measurements. Each independent instance is managed locally, but able to federate on a global scale; enabling a full view of the network infrastructure that spans domain boundaries. This information, available through web service interfaces, can easily be retrieved to create customized applications. USATLAS has developed a centralized “dashboard” offering network administrators, users, and decision makers the ability to see the performance of the network at a glance. The dashboard framework includes the ability to notify users (alarm) when problems are found, thus allowing rapid response to potential problems and making perfSONAR-PS crucial to the operation of our distributed computing infrastructure.

  2. A Persistent Back-End for the ATLAS Online Information Service (P-BEAST)

    CERN Document Server

    SICOE, A D; The ATLAS collaboration; KOLOS, S; MAGNONI, L; SOLOVIEV, I

    2012-01-01

    This poster describes P-BEAST, a highly scalable, highly available and durable system for archiving monitoring information of the trigger and data acquisition (TDAQ) system of the ATLAS experiment. Currently this consists of 20,000 applications running on 2,400 interconnected computers but it is foreseen to grow further in the near future. P-BEAST stores considerable amounts of monitoring information which would otherwise be lost. Making this data accessible, facilitates long term analysis and faster debugging. The novelty of this research consists of using a modern key-value storage technology (Cassandra) to satisfy the large time series data rates, flexibility and scalability requirements entailed by the project. The loose schema allows the stored data to evolve seamlessly with the information flowing within the Information Service. An architectural overview of P-BEAST is presented together with a discussion on the arguments which ultimately lead to choosing Cassandra as the storage technology. Measurements...

  3. Implementation and performance of the ATLAS pixel clustering neural networks

    CERN Document Server

    Gagnon, Louis-Guillaume; The ATLAS collaboration

    2018-01-01

    The high particle densities produced by the Large Hadron Collider (LHC) mean that in the ATLAS pixel detector the clusters of deposited charge start to merge. A neural network-based approach is used to estimate the number of particles contributing to each cluster, and to accurately estimate the hit positions even in the presence of multiple particles. This talk thoroughly describes the algorithm and its implementation as well as present a set of benchmark performance measurements. The problem is most acute in the core of high-momentum jets where the average separation between particles becomes comparable to the detector granularity. This is further complicated by the high number of interactions per bunch crossing. Both these issues will become worse as the Run 3 and HL-LHC programme require analysis of higher and higher pT jets, while the interaction multiplicity rises. Future prospects in the context of LHC Run 3 and the upcoming ATLAS inner detector upgrade are also discussed.

  4. The Run Control System and the Central Hint and Information Processor of the Data Acquisition System of the ATLAS Experiment at the LHC

    CERN Document Server

    Anders, G; The ATLAS collaboration; Lehmann Miotto, G; Magnoni, L

    2014-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector is composed of a large number of distributed hardware and software components (about 3000 machines and more than 15000 concurrent processes at the end of LHC’s Run I) which in a coordinated manner provide the data-taking functionality of the overall system. The Run Control (RC) system steers the data acquisition by starting and stopping processes and by carrying all data-taking elements through well-defined states in a coherent way (finite state machine pattern). The RC is organized as a hierarchical tree (run control tree) of run controllers following the functional de-composition into systems and sub-systems of the ATLAS detector. During the LHC Long Shutdown 1 (LS1) the RC has been completely re-designed and re-implemented in order to better fulfill the new requirements which emerged during the LHC Run 1 and were not foreseen during the initial design phase, and in order to improve the error management and recovery mechanisms. Indeed gi...

  5. Robustness of the ATLAS pixel clustering neural network algorithm

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration

    2016-01-01

    Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. The algorithms depend heavily on accurate estimation of the position of particles as they traverse the inner detector elements. An artificial neural network algorithm is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The method recovers otherwise lost tracks in dense environments where particles are separated by distances comparable to the size of the detector read-out elements. Such environments are highly relevant for LHC run 2, e.g. in searches for heavy resonances. Within the scope of run 2 track reconstruction performance and upgrades, the robustness of the neural network algorithm will be presented. The robustness has been studied by evaluating the stability of the algorithm’s performance under a range of variations in the pixel detector conditions.

  6. Neural network based cluster creation in the ATLAS silicon pixel detector

    CERN Document Server

    Selbach, K E; The ATLAS collaboration

    2012-01-01

    The read-out from individual pixels on planar semi-conductor sensors are grouped into clusters to reconstruct the location where a charged particle passed through the sensor. The resolution given by individual pixel sizes is significantly improved by using the information from the charge sharing between pixels. Such analog cluster creation techniques have been used by the ATLAS experiment for many years to obtain an excellent performance. However, in dense environments, such as those inside high-energy jets, clusters have an increased probability of merging the charge deposited by multiple particles. Recently, a neural network based algorithm which estimates both the cluster position and whether a cluster should be split has been developed for the ATLAS pixel detector. The algorithm significantly reduces ambiguities in the assignment of pixel detector measurement to tracks within jets and improves the position accuracy with respect to standard interpolation techniques by taking into account the 2-dimensional ...

  7. Neural network based cluster creation in the ATLAS silicon Pixel Detector

    CERN Document Server

    Andreazza, A; The ATLAS collaboration

    2013-01-01

    The read-out from individual pixels on planar semi-conductor sensors are grouped into clusters to reconstruct the location where a charged particle passed through the sensor. The resolution given by individual pixel sizes is significantly improved by using the information from the charge sharing between pixels. Such analog cluster creation techniques have been used by the ATLAS experiment for many years to obtain an excellent performance. However, in dense environments, such as those inside high-energy jets, clusters have an increased probability of merging the charge deposited by multiple particles. Recently, a neural network based algorithm which estimates both the cluster position and whether a cluster should be split has been developed for the ATLAS Pixel Detector. The algorithm significantly reduces ambiguities in the assignment of pixel detector measurement to tracks within jets and improves the position accuracy with respect to standard interpolation techniques by taking into account the 2-dimensional ...

  8. Atlas of three-dimensional gridded fields obtained from the radiosonde network during PYREX. 2. ed.

    International Nuclear Information System (INIS)

    Volkert, H.; Schumann, U.

    1994-01-01

    During the Pyrenees Experiment (PYREX) in October and November 1990 in radiosonde network was in operation with enhanced spatial and temporal resolution. This atlas contains standardized output from a three-dimensional, objective analysis scheme which is used to interpolate from the observed significant levels to a regular grid centred over the Pyrenees. For each of the 68 release times during ten intensive observation periods 12 horizontal charts are displayed on one page. These charts contain temperature, relative humidity or potential vorticity, and horizontal wind (vectors and isotachs) in four levels. The atlas is considered as basic material for more detailed studies at or between selected release times. (orig.) [de

  9. First experiences with the ATLAS pixel detector control system at the combined test beam 2004

    International Nuclear Information System (INIS)

    Imhaeuser, Martin; Becks, Karl-Heinz; Henss, Tobias; Kersten, Susanne; Maettig, Peter; Schultes, Joachim

    2006-01-01

    Detector control systems (DCS) include the readout, control and supervision of hardware devices as well as the monitoring of external systems like cooling system and the processing of control data. The implementation of such a system in the final experiment also has to provide the communication with the trigger and data acquisition system (TDAQ). In addition, conditions data which describe the status of the pixel detector modules and their environment must be logged and stored in a common LHC wide database system. At the combined test beam all ATLAS subdetectors were operated together for the first time over a longer period. To ensure the functionality of the pixel detector, a control system was set up. We describe the architecture chosen for the pixel DCS, the interfaces to hardware devices, the interfaces to the users and the performance of our system. The embedding of the DCS in the common infrastructure of the combined test beam and also its communication with surrounding systems will be discussed in some detail

  10. Network Neurodegeneration in Alzheimer’s Disease via MRI based Shape Diffeomorphometry and High Field Atlasing

    Directory of Open Access Journals (Sweden)

    Michael I Miller

    2015-05-01

    Full Text Available This paper examines MRI analysis of neurodegeneration in Alzheimer’s Disease (AD in a network of structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing in which the entorhinal cortex is partitioned into nine subareas. The morphometry markers for three groups of subjects (controls, preclinical AD and symptomatic AD are indexed to template coordinates measured with respect to these nine subareas. The location and timing of changes are examined within the subareas as it pertains to the classic Braak and Braak staging by comparing the three groups. We demonstrate that the earliest preclinical changes in the population occur in the lateral most sulcal extent in the entorhinal cortex (alluded to as trans entorhinal cortex by Braak and Braak, and then proceeds medially which is consistent with the Braak and Braak staging. We use high field 11T atlasing to demonstrate that the network changes are occurring at the junctures of the substructures in this medial temporal lobe network. Temporal progression of the disease through the network is also examined via changepoint analysis demonstrating earliest changes in entorhinal cortex. The differential expression of rate of atrophy with progression signaling the changepoint time across the network is demonstrated to be signaling in the intermediate caudal subarea of the entorhinal cortex, which has been noted to be proximal to the hippocampus. This coupled to the findings of the nearby basolateral involvement in amygdala demonstrates the selectivity of neurodegeneration in early AD.

  11. ATLAS DataFlow Infrastructure recent results from ATLAS cosmic and first-beam data-taking

    CERN Document Server

    Vandelli, W

    2010-01-01

    The ATLAS DataFlow infrastructure is responsible for the collection and conveyance of event data from the detector front-end electronics to the mass storage. Several optimized and multi-threaded applications fulfill this purpose operating over a multi-stage Gigabit Ethernet network which is the backbone of the ATLAS Trigger and Data Acquisition System. The system must be able to efficiently transport event-data with high reliability, while providing aggregated bandwidths larger than 5 GByte/s and coping with many thousands network connections. Nevertheless, routing and streaming capabilities and monitoring and data accounting functionalities are also fundamental requirements. During 2008, a few months of ATLAS cosmic data-taking and the first experience with the LHC beams provided an unprecedented testbed for the evaluation of the performance of the ATLAS DataFlow, in terms of functionality, robustness and stability. Besides, operating the system far from its design specifications helped in exercising its fle...

  12. ATLAS DataFlow Infrastructure: Recent results from ATLAS cosmic and first-beam data-taking

    Energy Technology Data Exchange (ETDEWEB)

    Vandelli, Wainer, E-mail: wainer.vandelli@cern.c

    2010-04-01

    The ATLAS DataFlow infrastructure is responsible for the collection and conveyance of event data from the detector front-end electronics to the mass storage. Several optimized and multi-threaded applications fulfill this purpose operating over a multi-stage Gigabit Ethernet network which is the backbone of the ATLAS Trigger and Data Acquisition System. The system must be able to efficiently transport event-data with high reliability, while providing aggregated bandwidths larger than 5 GByte/s and coping with many thousands network connections. Nevertheless, routing and streaming capabilities and monitoring and data accounting functionalities are also fundamental requirements. During 2008, a few months of ATLAS cosmic data-taking and the first experience with the LHC beams provided an unprecedented test-bed for the evaluation of the performance of the ATLAS DataFlow, in terms of functionality, robustness and stability. Besides, operating the system far from its design specifications helped in exercising its flexibility and contributed in understanding its limitations. Moreover, the integration with the detector and the interfacing with the off-line data processing and management have been able to take advantage of this extended data taking-period as well. In this paper we report on the usage of the DataFlow infrastructure during the ATLAS data-taking. These results, backed-up by complementary performance tests, validate the architecture of the ATLAS DataFlow and prove that the system is robust, flexible and scalable enough to cope with the final requirements of the ATLAS experiment.

  13. ATLAS DataFlow Infrastructure: Recent results from ATLAS cosmic and first-beam data-taking

    International Nuclear Information System (INIS)

    Vandelli, Wainer

    2010-01-01

    The ATLAS DataFlow infrastructure is responsible for the collection and conveyance of event data from the detector front-end electronics to the mass storage. Several optimized and multi-threaded applications fulfill this purpose operating over a multi-stage Gigabit Ethernet network which is the backbone of the ATLAS Trigger and Data Acquisition System. The system must be able to efficiently transport event-data with high reliability, while providing aggregated bandwidths larger than 5 GByte/s and coping with many thousands network connections. Nevertheless, routing and streaming capabilities and monitoring and data accounting functionalities are also fundamental requirements. During 2008, a few months of ATLAS cosmic data-taking and the first experience with the LHC beams provided an unprecedented test-bed for the evaluation of the performance of the ATLAS DataFlow, in terms of functionality, robustness and stability. Besides, operating the system far from its design specifications helped in exercising its flexibility and contributed in understanding its limitations. Moreover, the integration with the detector and the interfacing with the off-line data processing and management have been able to take advantage of this extended data taking-period as well. In this paper we report on the usage of the DataFlow infrastructure during the ATLAS data-taking. These results, backed-up by complementary performance tests, validate the architecture of the ATLAS DataFlow and prove that the system is robust, flexible and scalable enough to cope with the final requirements of the ATLAS experiment.

  14. ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software.

    Science.gov (United States)

    Jacomy, Mathieu; Venturini, Tommaso; Heymann, Sebastien; Bastian, Mathieu

    2014-01-01

    Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics...). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users' typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.

  15. Robustness of the Artificial Neural Networks Used for Clustering in the ATLAS Pixel Detector

    CERN Document Server

    The ATLAS collaboration

    2015-01-01

    A study of the robustness of the ATLAS pixel neural network clustering algorithm is presented. The sensitivity to variations to its input is evaluated. These variations are motivated by potential discrepancies between data and simulation due to uncertainties in the modelling of pixel clusters in simulation, as well as uncertainties from the detector calibration. Within reasonable variation magnitudes, the neural networks prove to be robust to most variations. The neural network used to identify pixel clusters created by multiple charged particles, is most sensitive to variations affecting the total amount of charge collected in the cluster. Modifying the read-out threshold has the biggest effect on the clustering's ability to estimate the position of the particle's intersection with the detector.

  16. ATLAS@Home looks for CERN volunteers

    CERN Multimedia

    Rosaria Marraffino

    2014-01-01

    ATLAS@Home is a CERN volunteer computing project that runs simulated ATLAS events. As the project ramps up, the project team is looking for CERN volunteers to test the system before planning a bigger promotion for the public.   The ATLAS@home outreach website. ATLAS@Home is a large-scale research project that runs ATLAS experiment simulation software inside virtual machines hosted by volunteer computers. “People from all over the world offer up their computers’ idle time to run simulation programmes to help physicists extract information from the large amount of data collected by the detector,” explains Claire Adam Bourdarios of the ATLAS@Home project. “The ATLAS@Home project aims to extrapolate the Standard Model at a higher energy and explore what new physics may look like. Everything we’re currently running is preparation for next year's run.” ATLAS@Home became an official BOINC (Berkeley Open Infrastructure for Network ...

  17. Use of modeling to assess the scalability of Ethernet networks for the ATLAS second level trigger

    CERN Document Server

    Korcyl, K; Dobinson, Robert W; Saka, F

    1999-01-01

    The second level trigger of LHC's ATLAS experiment has to perform real-time analyses on detector data at 10 GBytes/s. A switching network is required to connect more than thousand read-out buffers to about thousand processors that execute the trigger algorithm. We are investigating the use of Ethernet technology to build this large switching network. Ethernet is attractive because of the huge installed base, competitive prices, and recent introduction of the high-performance Gigabit version. Due to the network's size it has to be constructed as a layered structure of smaller units. To assess the scalability of such a structure we evaluated a single switch unit. (0 refs).

  18. The Associative Memory Serial Link Processor of the ALTAS Fast TracKer Processing System

    CERN Document Server

    Sotiropoulou, Calliope Louisa; The ATLAS collaboration

    2017-01-01

    The upgraded Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at the LHC will improve the capability of the detector to select the events with the greatest scientific potential. The Fast TracKer (FTK) is one of the ATLAS TDAQ upgrades that is presently under commissioning. FTK is a custom hardware system that feeds the High Level Trigger (HLT) with charged particle tracks reconstructed from hits in silicon detectors at the rate of 105 events per second. The main processing element of FTK is the Associative Memory (AM) system that is used to perform pattern matching with a high degree of parallelism. Its implementation is called the AM Board Serial Link Processor (AMBSLP) and it is a very efficient pattern matching machine that handles in parallel massive data samples. The AMBSLP consists of two types of boards: the Little Associative Memory Board (LAMB), a mezzanine where the AM chips are mounted, and the Associative Memory Board (AMB), a 9U VME motherboard that hosts four LAMB daughter-boar...

  19. Event streaming in the online system

    CERN Document Server

    Klous, S; The ATLAS collaboration

    2010-01-01

    The Large Hadron Collider (LHC), currently in operation at CERN in Geneva, is a circular 27-kilometer-circumference machine, accelerating bunches of protons in opposite directions. The bunches will cross at four different interaction points with a bunch-crossing frequency of 40MHz. ATLAS, the largest LHC experiment, registers the signals induced by particles traversing the detector components on each bunch crossing. When this happens a total of around 1.5MB of data are collected. This results in a data rate of around 60 TB/s flowing out of the detector. Note that the available event storage space is limited to about 6 PB per year. With an operational period of about 20 million seconds per year, this requires a data reduction factor of 200:000 in the trigger and data acquisition (TDAQ) system. Events included in the recording rate budget are already subdivided and organized by ATLAS during data acquisition. So, the TDAQ system does not only take care of data reduction, but also organizes the collected events. ...

  20. ATLAS Grid Workflow Performance Optimization

    CERN Document Server

    Elmsheuser, Johannes; The ATLAS collaboration

    2018-01-01

    The CERN ATLAS experiment grid workflow system manages routinely 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 300 PB of data is distributed over more than 150 sites in the WLCG. At this scale small improvements in the software and computing performance and workflows can lead to significant resource usage gains. ATLAS is reviewing together with CERN IT experts several typical simulation and data processing workloads for potential performance improvements in terms of memory and CPU usage, disk and network I/O. All ATLAS production and analysis grid jobs are instrumented to collect many performance metrics for detailed statistical studies using modern data analytics tools like ElasticSearch and Kibana. This presentation will review and explain the performance gains of several ATLAS simulation and data processing workflows and present analytics studies of the ATLAS grid workflows.

  1. Identification of Jets Containing b-Hadrons with Recurrent Neural Networks at the ATLAS Experiment

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    A novel b-jet identification algorithm is constructed with a Recurrent Neural Network (RNN) at the ATLAS Experiment. This talk presents the expected performance of the RNN based b-tagging in simulated $t \\bar t$ events. The RNN based b-tagging processes properties of tracks associated to jets which are represented in sequences. In contrast to traditional impact-parameter-based b-tagging algorithms which assume the tracks of jets are independent from each other, RNN based b-tagging can exploit the spatial and kinematic correlations of tracks which are initiated from the same b-hadrons. The neural network nature of the tagging algorithm also allows the flexibility of extending input features to include more track properties than can be effectively used in traditional algorithms.

  2. Studies of ATM for ATLAS high-level triggers

    CERN Document Server

    Bystrický, J; Huet, M; Le Dû, P; Mandjavidze, I D

    2001-01-01

    This paper presents some of the conclusions of our studies on asynchronous transfer mode (ATM) and fast Ethernet in the ATLAS level-2 trigger pilot project. We describe the general concept and principles of our data-collection and event-building scheme that could be transposed to various experiments in high-energy and nuclear physics. To validate the approach in view of ATLAS high-level triggers, we assembled a testbed composed of up to 48 computers linked by a 7.5-Gbit/s ATM switch. This modular switch is used as a single entity or is split into several smaller interconnected switches. This allows study of how to construct a large network from smaller units. Alternatively, the ATM network can be replaced by fast Ethernet. We detail the operation of the system and present series of performance measurements made with event-building traffic pattern. We extrapolate these results to show how today's commercial networking components could be used to build a 1000-port network adequate for ATLAS needs. Lastly, we li...

  3. ICN_Atlas: Automated description and quantification of functional MRI activation patterns in the framework of intrinsic connectivity networks.

    Science.gov (United States)

    Kozák, Lajos R; van Graan, Louis André; Chaudhary, Umair J; Szabó, Ádám György; Lemieux, Louis

    2017-12-01

    Generally, the interpretation of functional MRI (fMRI) activation maps continues to rely on assessing their relationship to anatomical structures, mostly in a qualitative and often subjective way. Recently, the existence of persistent and stable brain networks of functional nature has been revealed; in particular these so-called intrinsic connectivity networks (ICNs) appear to link patterns of resting state and task-related state connectivity. These networks provide an opportunity of functionally-derived description and interpretation of fMRI maps, that may be especially important in cases where the maps are predominantly task-unrelated, such as studies of spontaneous brain activity e.g. in the case of seizure-related fMRI maps in epilepsy patients or sleep states. Here we present a new toolbox (ICN_Atlas) aimed at facilitating the interpretation of fMRI data in the context of ICN. More specifically, the new methodology was designed to describe fMRI maps in function-oriented, objective and quantitative way using a set of 15 metrics conceived to quantify the degree of 'engagement' of ICNs for any given fMRI-derived statistical map of interest. We demonstrate that the proposed framework provides a highly reliable quantification of fMRI activation maps using a publicly available longitudinal (test-retest) resting-state fMRI dataset. The utility of the ICN_Atlas is also illustrated on a parametric task-modulation fMRI dataset, and on a dataset of a patient who had repeated seizures during resting-state fMRI, confirmed on simultaneously recorded EEG. The proposed ICN_Atlas toolbox is freely available for download at http://icnatlas.com and at http://www.nitrc.org for researchers to use in their fMRI investigations. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  4. The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

    International Nuclear Information System (INIS)

    Kazarov, A; Miotto, G Lehmann; Magnoni, L

    2012-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for collecting and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This requires strong competence and experience in understanding and discovering problems and root causes, and often the meaningful information is not in the single message or update, but in the aggregated behavior in a certain time-line. The AAL project is meant at reducing the man power needs and at assuring a constant high quality of problem detection by automating most of the monitoring tasks and providing real-time correlation of data-taking and system metrics. This project combines technologies coming from different disciplines, in particular it leverages on an Event Driven Architecture to unify the flow of data from the ATLAS infrastructure, on a Complex Event Processing (CEP) engine for correlation of events and on a message oriented architecture for components integration. The project is composed of 2 main components: a core processing engine, responsible for correlation of events through expert-defined queries and a web based front-end to present real-time information and interact with the system. All components works in a loose-coupled event based architecture, with a message broker

  5. The AAL project: automated monitoring and intelligent analysis for the ATLAS data taking infrastructure

    Science.gov (United States)

    Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

    2012-06-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment at CERN is the infrastructure responsible for collecting and transferring ATLAS experimental data from detectors to the mass storage system. It relies on a large, distributed computing environment, including thousands of computing nodes with thousands of application running concurrently. In such a complex environment, information analysis is fundamental for controlling applications behavior, error reporting and operational monitoring. During data taking runs, streams of messages sent by applications via the message reporting system together with data published from applications via information services are the main sources of knowledge about correctness of running operations. The flow of data produced (with an average rate of O(1-10KHz)) is constantly monitored by experts to detect problem or misbehavior. This requires strong competence and experience in understanding and discovering problems and root causes, and often the meaningful information is not in the single message or update, but in the aggregated behavior in a certain time-line. The AAL project is meant at reducing the man power needs and at assuring a constant high quality of problem detection by automating most of the monitoring tasks and providing real-time correlation of data-taking and system metrics. This project combines technologies coming from different disciplines, in particular it leverages on an Event Driven Architecture to unify the flow of data from the ATLAS infrastructure, on a Complex Event Processing (CEP) engine for correlation of events and on a message oriented architecture for components integration. The project is composed of 2 main components: a core processing engine, responsible for correlation of events through expert-defined queries and a web based front-end to present real-time information and interact with the system. All components works in a loose-coupled event based architecture, with a message broker

  6. National Transportation Atlas Databases : 2012.

    Science.gov (United States)

    2012-01-01

    The National Transportation Atlas Databases 2012 (NTAD2012) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  7. National Transportation Atlas Databases : 2011.

    Science.gov (United States)

    2011-01-01

    The National Transportation Atlas Databases 2011 (NTAD2011) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  8. National Transportation Atlas Databases : 2009.

    Science.gov (United States)

    2009-01-01

    The National Transportation Atlas Databases 2009 (NTAD2009) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  9. National Transportation Atlas Databases : 2010.

    Science.gov (United States)

    2010-01-01

    The National Transportation Atlas Databases 2010 (NTAD2010) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  10. National Transportation Atlas Databases : 2013.

    Science.gov (United States)

    2013-01-01

    The National Transportation Atlas Databases 2013 (NTAD2013) is a set of nationwide geographic datasets of transportation facilities, transportation networks, associated infrastructure, and other political and administrative entities. These datasets i...

  11. National Transportation Atlas Databases : 2015.

    Science.gov (United States)

    2015-01-01

    The National Transportation Atlas Databases 2015 (NTAD2015) is a set of nationwide geographic datasets of transportation facilities, transportation networks, associated infrastructure, and other political and administrative entities. These datasets i...

  12. National Transportation Atlas Databases : 2014.

    Science.gov (United States)

    2014-01-01

    The National Transportation Atlas Databases 2014 (NTAD2014) is a set of nationwide geographic datasets of transportation facilities, transportation networks, associated infrastructure, and other political and administrative entities. These datasets i...

  13. Improvement in separation of isolated muons and pions at low pT in ATLAS hadron calorimeter using artificial neural networks technique

    International Nuclear Information System (INIS)

    Astvatsaturov, A.; Budagov, Yu.; Chirikov-Zorin, I.; Shigaev, V.; Paplevka, A.; Sushkov, S.; Bosman, M.; Nessi, M.

    1995-01-01

    Advantages of artificial neural networks techniques in handling data from highly granulated ATLAS hadron calorimeter (HC) are shown in application to isolated π/μ separation task in the range 3 T T muons have a significant probability to be absorbed in the calorimeter and therefore they cannot be reliably registered by the muon detector. The comparative analysis of main characteristics is presented for several neural net discriminators and a linear threshold discriminator operating on energy deposition in the last depth of HC. The analysis is based on MC data obtained with ATLAS simulation programs. 9 refs., 12 figs

  14. The use of Ethernet in the DataFlow of the ATLAS Trigger & DAQ

    CERN Document Server

    Stancu, Stefan; Dobinson, Bob; Korcyl, Krzysztof; Knezo, Emil; CHEP 2003 Computing in High Energy Physics

    2003-01-01

    The article analyzes a proposed network topology for the ATLAS DAQ DataFlow, and identifies the Ethernet features required for a proper operation of the network: MAC address table size, switch performance in terms of throughput and latency, the use of Flow Control, Virtual LANs and Quality of Service. We investigate these features on some Ethernet switches, and conclude on their usefulness for the ATLAS DataFlow network

  15. Expression atlas and comparative coexpression network analyses reveal important genes involved in the formation of lignified cell wall in Brachypodium distachyon.

    Science.gov (United States)

    Sibout, Richard; Proost, Sebastian; Hansen, Bjoern Oest; Vaid, Neha; Giorgi, Federico M; Ho-Yue-Kuang, Severine; Legée, Frédéric; Cézart, Laurent; Bouchabké-Coussa, Oumaya; Soulhat, Camille; Provart, Nicholas; Pasha, Asher; Le Bris, Philippe; Roujol, David; Hofte, Herman; Jamet, Elisabeth; Lapierre, Catherine; Persson, Staffan; Mutwil, Marek

    2017-08-01

    While Brachypodium distachyon (Brachypodium) is an emerging model for grasses, no expression atlas or gene coexpression network is available. Such tools are of high importance to provide insights into the function of Brachypodium genes. We present a detailed Brachypodium expression atlas, capturing gene expression in its major organs at different developmental stages. The data were integrated into a large-scale coexpression database ( www.gene2function.de), enabling identification of duplicated pathways and conserved processes across 10 plant species, thus allowing genome-wide inference of gene function. We highlight the importance of the atlas and the platform through the identification of duplicated cell wall modules, and show that a lignin biosynthesis module is conserved across angiosperms. We identified and functionally characterised a putative ferulate 5-hydroxylase gene through overexpression of it in Brachypodium, which resulted in an increase in lignin syringyl units and reduced lignin content of mature stems, and led to improved saccharification of the stem biomass. Our Brachypodium expression atlas thus provides a powerful resource to reveal functionally related genes, which may advance our understanding of important biological processes in grasses. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

  16. FELIX: a High-Throughput Network Approach for Interfacing to Front End Electronics for ATLAS Upgrades

    International Nuclear Information System (INIS)

    Anderson, J; Drake, G; Ryu, S; Zhang, J; Borga, A; Boterenbrood, H; Schreuder, F; Vermeulen, J; Chen, H; Chen, K; Lanni, F; Francis, D; Gorini, B; Miotto, G Lehmann; Schumacher, J; Vandelli, W; Levinson, L; Narevicius, J; Roich, A; Plessl, C

    2015-01-01

    The ATLAS experiment at CERN is planning full deployment of a new unified optical link technology for connecting detector front end electronics on the timescale of the LHC Run 4 (2025). It is estimated that roughly 8000 GBT (GigaBit Transceiver) links, with transfer rates up to 10.24 Gbps, will replace existing links used for readout, detector control and distribution of timing and trigger information. A new class of devices will be needed to interface many GBT links to the rest of the trigger, data-acquisition and detector control systems. In this paper FELIX (Front End LInk eXchange) is presented, a PC-based device to route data from and to multiple GBT links via a high-performance general purpose network capable of a total throughput up to O(20 Tbps). FELIX implies architectural changes to the ATLAS data acquisition system, such as the use of industry standard COTS components early in the DAQ chain. Additionally the design and implementation of a FELIX demonstration platform is presented and hardware and software aspects will be discussed. (paper)

  17. An Ensemble of Neural Networks for Online Electron Filtering at the ATLAS Experiment.

    CERN Document Server

    Da Fonseca Pinto, Joao Victor; The ATLAS collaboration

    2018-01-01

    In 2017 the ATLAS experiment implemented an ensemble of neural networks (NeuralRinger algorithm) dedicated to improving the performance of filtering events containing electrons in the high-input rate online environment of the Large Hadron Collider at CERN, Geneva. The ensemble employs a concept of calorimetry rings. The training procedure and final structure of the ensemble are used to minimize fluctuations from detector response, according to the particle energy and position of incidence. A detailed study was carried out to assess profile distortions in crucial offline quantities through the usage of statistical tests and residual analysis. These details and the online performance of this algorithm during the 2017 data-taking will be presented.

  18. Recent Workshops

    CERN Multimedia

    Wickens, F. J.

    Since the previous edition of ATLAS e-news, the NIKHEF Institute in Amsterdam has hosted not just one but two workshops related to ATLAS TDAQ activities. The first in October was dedicated to the Detector Control System (DCS). Just three institutes, CERN, NIKHEF and St Petersburg, provide the effort for the central DCS services, but each ATLAS sub-detector provides effort for their own controls. Some 30 people attended, including representatives for all of the ATLAS sub-detectors, representatives of the institutes working on the central services and the project leader of JCOP, which brings together common aspects of detector controls across the LHC experiments. During the three-day workshop the common components were discussed, and each sub-detector described their experiences and plans for their future systems. Whilst many of the components to be used are standard commercial components, a key custom item for ATLAS is the ELMB (Embedded Local Monitor Board). Prototypes for this have now been extensively test...

  19. Data federation strategies for ATLAS using XRootD

    Science.gov (United States)

    Gardner, Robert; Campana, Simone; Duckeck, Guenter; Elmsheuser, Johannes; Hanushevsky, Andrew; Hönig, Friedrich G.; Iven, Jan; Legger, Federica; Vukotic, Ilija; Yang, Wei; Atlas Collaboration

    2014-06-01

    In the past year the ATLAS Collaboration accelerated its program to federate data storage resources using an architecture based on XRootD with its attendant redirection and storage integration services. The main goal of the federation is an improvement in the data access experience for the end user while allowing more efficient and intelligent use of computing resources. Along with these advances come integration with existing ATLAS production services (PanDA and its pilot services) and data management services (DQ2, and in the next generation, Rucio). Functional testing of the federation has been integrated into the standard ATLAS and WLCG monitoring frameworks and a dedicated set of tools provides high granularity information on its current and historical usage. We use a federation topology designed to search from the site's local storage outward to its region and to globally distributed storage resources. We describe programmatic testing of various federation access modes including direct access over the wide area network and staging of remote data files to local disk. To support job-brokering decisions, a time-dependent cost-of-data-access matrix is made taking into account network performance and key site performance factors. The system's response to production-scale physics analysis workloads, either from individual end-users or ATLAS analysis services, is discussed.

  20. Exploitation of heterogeneous resources for ATLAS Computing

    CERN Document Server

    Chudoba, Jiri; The ATLAS collaboration

    2018-01-01

    LHC experiments require significant computational resources for Monte Carlo simulations and real data processing and the ATLAS experiment is not an exception. In 2017, ATLAS exploited steadily almost 3M HS06 units, which corresponds to about 300 000 standard CPU cores. The total disk and tape capacity managed by the Rucio data management system exceeded 350 PB. Resources are provided mostly by Grid computing centers distributed in geographically separated locations and connected by the Grid middleware. The ATLAS collaboration developed several systems to manage computational jobs, data files and network transfers. ATLAS solutions for job and data management (PanDA and Rucio) were generalized and now are used also by other collaborations. More components are needed to include new resources such as private and public clouds, volunteers' desktop computers and primarily supercomputers in major HPC centers. Workflows and data flows significantly differ for these less traditional resources and extensive software re...

  1. FELIX - the new detector readout system for the ATLAS experiment

    CERN Document Server

    AUTHOR|(SzGeCERN)754725; The ATLAS collaboration; Anderson, John Thomas; Borga, Andrea; Boterenbrood, Hendrik; Chen, Hucheng; Chen, Kai; Drake, Gary; Donszelmann, Mark; Francis, David; Gorini, Benedetto; Guest, Daniel; Lanni, Francesco; Lehmann Miotto, Giovanna; Levinson, Lorne; Roich, Alexander; Schreuder, Frans Philip; Schumacher, J\\"orn; Vandelli, Wainer; Vermeulen, Jos; Wu, Weihao; Zhang, Jinlong

    2016-01-01

    From the ATLAS Phase-I upgrade and onward, new or upgraded detectors and trigger systems will be interfaced to the data acquisition, detector control and timing (TTC) systems by the Front-End Link eXchange (FELIX). FELIX is the core of the new ATLAS Trigger/DAQ architecture. Functioning as a router between custom serial links and a commodity network, FELIX is implemented by server PCs with commodity network interfaces and PCIe cards with large FPGAs and many high speed serial fiber transceivers. By separating data transport from data manipulation, the latter can be done by software in commodity servers attached to the network. Replacing traditional point-to-point links between Front-end components and the DAQ system by a switched network, FELIX provides scaling, flexibility uniformity and upgradability. Different Front-end data types or different data sources can be routed to different network endpoints that handle that data type or source: e.g. event data, configuration, calibration, detector control, monito...

  2. The LUCID detector

    CERN Document Server

    Lasagni Manghi, Federico; The ATLAS collaboration

    2015-01-01

    Starting from 2015 LHC will perform a new run, at higher center of mass energy (13 TeV) and with 25 ns bunch-spacing. The ATLAS luminosity monitor LUCID has been completely renewed, both on detector design and in the electronics, in order to cope with the new running conditions. The new detector electronics is presented, featuring a new read-out board (LUCROD), for signal acquisition and digitization, PMT-charge integration and single-side luminosity measurements, and the revisited LUMAT board for side A–side C combination. The contribution covers the new boards design, the firmware and software developments, the implementation of luminosity algorithms, the optical communication between boards and the integration into the ATLAS TDAQ system.

  3. Studies for the detector control system of the ATLAS pixel at the HL-LHC

    International Nuclear Information System (INIS)

    Püllen, L; Becker, K; Boek, J; Kersten, S; Kind, P; Mättig, P; Zeitnitz, C

    2012-01-01

    In the context of the LHC upgrade to the HL-LHC the inner detector of the ATLAS experiment will be replaced completely. As part of this redesign there will also be a new pixel detector. This new pixel detector requires a control system which meets the strict space requirements for electronics in the ATLAS experiment. To accomplish this goal we propose a DCS (Detector Control System) network with the smallest form factor currently available. This network consists of a DCS chip located in close proximity to the interaction point and a DCS controller located in the outer regions of the ATLAS detector. These two types of chips form a star shaped network with several DCS chips being controlled by one DCS controller. Both chips are manufactured in deep sub-micron technology. We present prototypes with emphasis on studies concerning single event upsets.

  4. Data federation strategies for ATLAS using XRootD

    International Nuclear Information System (INIS)

    Gardner, Robert; Vukotic, Ilija; Campana, Simone; Iven, Jan; Duckeck, Guenter; Elmsheuser, Johannes; Hönig, Friedrich G; Legger, Federica; Hanushevsky, Andrew; Yang, Wei

    2014-01-01

    In the past year the ATLAS Collaboration accelerated its program to federate data storage resources using an architecture based on XRootD with its attendant redirection and storage integration services. The main goal of the federation is an improvement in the data access experience for the end user while allowing more efficient and intelligent use of computing resources. Along with these advances come integration with existing ATLAS production services (PanDA and its pilot services) and data management services (DQ2, and in the next generation, Rucio). Functional testing of the federation has been integrated into the standard ATLAS and WLCG monitoring frameworks and a dedicated set of tools provides high granularity information on its current and historical usage. We use a federation topology designed to search from the site's local storage outward to its region and to globally distributed storage resources. We describe programmatic testing of various federation access modes including direct access over the wide area network and staging of remote data files to local disk. To support job-brokering decisions, a time-dependent cost-of-data-access matrix is made taking into account network performance and key site performance factors. The system's response to production-scale physics analysis workloads, either from individual end-users or ATLAS analysis services, is discussed.

  5. Master of Puppets

    CERN Document Server

    Ballestrero, Sergio; The ATLAS collaboration; Fazio, Daniel; Gament, Costin-Eugen; Lee, Christopher; Scannicchio, Diana; Twomey, Matthew Shaun

    2016-01-01

    Within the ATLAS detector, the Trigger and Data Acquisition system is responsible for the online processing of data streamed from the detector during collisions at the Large Hadron Collider at CERN. The online farm is comprised of ~4000 servers processing the data read out from ~100 million detector channels through multiple trigger levels. Configuring of these servers is not an easy task, especially since the detector itself is made up of multiple different sub-detectors, each with their own particular requirements. The previous method of configuring these servers, using Quattor and a hierarchical scripts system was cumbersome and restrictive. A better, unified system was therefore required to simplify the tasks of the TDAQ Systems Administrators, for both the local and net booted systems, and to be able to fulfil the requirements of TDAQ, Detector Control Systems and the sub-detectors groups. Various configuration management systems were evaluated, though in the end, Puppet was chosen as the application of ...

  6. Pre-Cancer Atlas (PCA) and Other Human Tumor Atlas Network (HTAN) Funding Opportunity Announcements (FOAs) Released | Division of Cancer Prevention

    Science.gov (United States)

    There are 3 new funding opportunity announcements about the Pre-Cancer Atlas associated with the Beau Biden Cancer MoonshotSM Initiative that are intended to accelerate cancer research. The purpose of the FOAs is to promote research that results in a comprehensive view of the dynamic, multidimensional tumor ecosystem and is a direct response to the Moonshot Blue Ribbon Panel recommendation to generate human tumor atlases. |

  7. The Measurement of Spectral Characteristics and Composition of Radiation in Atlas with MEDIPIX2-USB Devices

    Science.gov (United States)

    Campbell, M.; Doležal, Z.; Greiffenberg, D.; Heijne, E.; Holy, T.; Idárraga, J.; Jakůbek, J.; Král, V.; Králík, M.; Lebel, C.; Leroy, C.; Llopart, X.; Lord, G.; Maneuski, D.; Ouellette, O.; Sochor, V.; Pospíšil, S.; Suk, M.; Tlustos, L.; Vykydal, Z.; Wilhelm, I.

    2008-06-01

    A network of devices to perform real-time measurements of the spectral characteristics and composition of radiation in the ATLAS detector and cavern during its operation is being built. This system of detectors will be a stand alone system fully capable of delivering real-time images of fluxes and spectral composition of different particle species including slow and fast neutrons. The devices are based on MEDIPIX2 pixel silicon detectors that will be operated via active USB cables and USB-Ethernet extenders through an Ethernet network by a PC located in the USA15 ATLAS control room. The installation of 14 devices inside ATLAS (detector and cavern) is in progress.

  8. The Measurement of Spectral Characteristics and Composition of Radiation in ATLAS with MEDIPIX2-USB Devices

    CERN Document Server

    Campbell, M.; Greiffenberg, D.; Heijne, E.; Holy, T.; Idárraga, J.; Jakubek, J.; Král, V.; Králík, M.; Lebel, C.; Leroy, C.; Llopart, X.; Lord, G.; Maneuski, D.; Ouellette, O.; Sochor, V.; Prospísil, S.; Suk, M; Tlustos, L.; Vykydal, Z.; Wilhelm, I.

    2008-01-01

    A network of devices to perform real-time measurements of the spectral characteristics and composition of radiation in the ATLAS detector and cavern during its operation is being built. This system of detectors will be a stand alone system fully capable of delivering real-time images of fluxes and spectral composition of different particle species including slow and fast neutrons. The devices are based on MEDIPIX2 pixel silicon detectors that will be operated via active USB cables and USB-Ethernet extenders through an Ethernet network by a PC located in the USA15 ATLAS control room. The installation of 14 devices inside ATLAS (detector and cavern) is in progress.

  9. Identification of Jets Containing $b$-Hadrons with Recurrent Neural Networks at the ATLAS Experiment

    CERN Document Server

    The ATLAS collaboration

    2017-01-01

    A novel $b$-jet identification algorithm is constructed with a Recurrent Neural Network (RNN) at the ATLAS experiment at the CERN Large Hadron Collider. The RNN based $b$-tagging algorithm processes charged particle tracks associated to jets without reliance on secondary vertex finding, and can augment existing secondary-vertex based taggers. In contrast to traditional impact-parameter-based $b$-tagging algorithms which assume that tracks associated to jets are independent from each other, the RNN based $b$-tagging algorithm can exploit the spatial and kinematic correlations between tracks which are initiated from the same $b$-hadrons. This new approach also accommodates an extended set of input variables. This note presents the expected performance of the RNN based $b$-tagging algorithm in simulated $t \\bar t$ events at $\\sqrt{s}=13$ TeV.

  10. World-wide online monitoring interface of the ATLAS experiment

    CERN Document Server

    Kolos, S; The ATLAS collaboration; Mineev, M; Hauser, R; Salnikov, A

    2014-01-01

    The ATLAS collaboration accounts for more than 3000 members located all over the world. The efficiency of the experiment can be improved allowing system experts not present on site to follow the ATLAS operations in real-time, spotting potential problems which otherwise may remain unattended for a non-negligible time. Taking into account the wide geographical spread of the ATLAS collaboration, the solution of this problem is to have all monitoring information with minimal access latency available world-wide. We have implemented a framework which defines a standard approach for retrieving arbitrary monitoring information from the ATLAS private network via HTTP. An information request is made by specifying one of the predefined URLs with some optional parameters refining data which has to be shipped back in XML format. The framework takes care of receiving, parsing and forwarding such requests to the appropriate plugins. The plugins retrieve the requested data and convert it to XML (or optionally to JSON) format...

  11. Multiple brain atlas database and atlas-based neuroimaging system.

    Science.gov (United States)

    Nowinski, W L; Fang, A; Nguyen, B T; Raphel, J K; Jagannathan, L; Raghavan, R; Bryan, R N; Miller, G A

    1997-01-01

    For the purpose of developing multiple, complementary, fully labeled electronic brain atlases and an atlas-based neuroimaging system for analysis, quantification, and real-time manipulation of cerebral structures in two and three dimensions, we have digitized, enhanced, segmented, and labeled the following print brain atlases: Co-Planar Stereotaxic Atlas of the Human Brain by Talairach and Tournoux, Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren, Referentially Oriented Cerebral MRI Anatomy by Talairach and Tournoux, and Atlas of the Cerebral Sulci by Ono, Kubik, and Abernathey. Three-dimensional extensions of these atlases have been developed as well. All two- and three-dimensional atlases are mutually preregistered and may be interactively registered with an actual patient's data. An atlas-based neuroimaging system has been developed that provides support for reformatting, registration, visualization, navigation, image processing, and quantification of clinical data. The anatomical index contains about 1,000 structures and over 400 sulcal patterns. Several new applications of the brain atlas database also have been developed, supported by various technologies such as virtual reality, the Internet, and electronic publishing. Fusion of information from multiple atlases assists the user in comprehensively understanding brain structures and identifying and quantifying anatomical regions in clinical data. The multiple brain atlas database and atlas-based neuroimaging system have substantial potential impact in stereotactic neurosurgery and radiotherapy by assisting in visualization and real-time manipulation in three dimensions of anatomical structures, in quantitative neuroradiology by allowing interactive analysis of clinical data, in three-dimensional neuroeducation, and in brain function studies.

  12. Network performance measurements as part of feasibility studies on moving an ATLAS event filter to off-site institutes

    CERN Document Server

    Korcyl, K; Dobinson, Robert W; Ivanovici, M; Losada-Maia, Marcia; Meirosu, C; Sladowski, G

    2004-01-01

    We present a system for measuring network performance as part of the feasibility studies for locating the ATLAS third level trigger, the event filter (EF), in remote locations. Part of the processing power required to run the EF algorithms, the current estimate is 2000 state off the art processors, can be provided in remote, CERN-affiliated institutes, if a suitable network connection between CERN and the remote site could be achieved. The system is composed of two PCs equipped with GPS systems, CERN-designed clock cards and Alteon gigabit programmable network interface cards. In the first set of measurements we plan to quantify connection in terms of end-to-end latency, throughput, jitter and packet loss. Running streaming tests and study throughput, IP QoS, routing testing and traffic shaping follows this. Finally, we plan to install the event filter software in a remote location and feed it with data from test beams at CERN. Each of these tests should be preformed with the test traffic treated in the netwo...

  13. Acacia Atlas 2005 | IDRC - International Development Research ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2010-12-13

    Dec 13, 2010 ... Acknowledgements. The maps presented in this atlas are only as good as the information provided to us, and we would like to thank the several dozens of network operators, regulators and policy makers who have generously contributed their knowledge, partner organisations which have granted ...

  14. Atlas – a data warehouse for integrative bioinformatics

    Directory of Open Access Journals (Sweden)

    Yuen Macaire MS

    2005-02-01

    Full Text Available Abstract Background We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. Description The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL calls that are implemented in a set of Application Programming Interfaces (APIs. The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD, Biomolecular Interaction Network Database (BIND, Database of Interacting Proteins (DIP, Molecular Interactions Database (MINT, IntAct, NCBI Taxonomy, Gene Ontology (GO, Online Mendelian Inheritance in Man (OMIM, LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. Conclusion The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First

  15. Sensitivity analysis of human brain structural network construction

    Directory of Open Access Journals (Sweden)

    Kuang Wei

    2017-12-01

    Full Text Available Network neuroscience leverages diffusion-weighted magnetic resonance imaging and tractography to quantify structural connectivity of the human brain. However, scientists and practitioners lack a clear understanding of the effects of varying tractography parameters on the constructed structural networks. With diffusion images from the Human Connectome Project (HCP, we characterize how structural networks are impacted by the spatial resolution of brain atlases, total number of tractography streamlines, and grey matter dilation with various graph metrics. We demonstrate how injudicious combinations of highly refined brain parcellations and low numbers of streamlines may inadvertently lead to disconnected network models with isolated nodes. Furthermore, we provide solutions to significantly reduce the likelihood of generating disconnected networks. In addition, for different tractography parameters, we investigate the distributions of values taken by various graph metrics across the population of HCP subjects. Analyzing the ranks of individual subjects within the graph metric distributions, we find that the ranks of individuals are affected differently by atlas scale changes. Our work serves as a guideline for researchers to optimize the selection of tractography parameters and illustrates how biological characteristics of the brain derived in network neuroscience studies can be affected by the choice of atlas parcellation schemes. Diffusion tractography has been proven to be a promising noninvasive technique to study the network properties of the human brain. However, how various tractography and network construction parameters affect network properties has not been studied using a large cohort of high-quality data. We utilize data provided by the Human Connectome Project to characterize the changes to network properties induced by varying the brain parcellation atlas scales, the number of reconstructed tractography tracks, and the degree of grey

  16. Evolution of the Atlas data and computing model for a Tier-2 in the EGI infrastructure

    CERN Document Server

    Fernandez, A; The ATLAS collaboration; AMOROS, G; VILLAPLANA, M; FASSI, F; KACI, M; LAMAS, A; OLIVER, E; SALT, J; SANCHEZ, J; SANCHEZ, V

    2012-01-01

    ABSTRAC ISCG 2012 Evolution of the Atlas data and computing model for a Tier2 in the EGI infrastructure During last years the Atlas computing model has moved from a more strict design, where every Tier2 had a liaison and a network dependence from a Tier1, to a more meshed approach where every cloud could be connected. Evolution of ATLAS data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. It also requires rethinking the network infrastructure to enable any Tier2 and associated Tier3 to easily connect to any Tier1 or Tier2. Tier2s are becoming more and more important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used more effic...

  17. FELIX: The New Approach for Interfacing to Front-end Electronics for the ATLAS Experiment

    CERN Document Server

    AUTHOR|(SzGeCERN)754725; The ATLAS collaboration; Anderson, John Thomas; Borga, Andrea; Boterenbrood, Hendrik; Chen, Hucheng; Chen, Kai; Drake, Gary; Donszelmann, Mark; Francis, David; Gorini, Benedetto; Guest, Daniel; Lanni, Francesco; Lehmann Miotto, Giovanna; Levinson, Lorne; Roich, Alexander; Schreuder, Frans Philip; Schumacher, J\\"orn; Vandelli, Wainer; Zhang, Jinlong

    2016-01-01

    From the ATLAS Phase-I upgrade and onward, new or upgraded detectors and trigger systems will be interfaced to the data acquisition, detector control and timing (TTC) systems by the Front-End Link eXchange (FELIX). FELIX is the core of the new ATLAS Trigger/DAQ architecture. Functioning as a router between custom serial links and a commodity network, FELIX is implemented by server PCs with commodity network interfaces and PCIe cards with large FPGAs and many high speed serial fiber transceivers. By separating data transport from data manipulation, the latter can be done by software in commodity servers attached to the network. Replacing traditional point-to-point links between Front-end components and the DAQ system by a switched network, FELIX provides scaling, flexibility uniformity and upgradability and reduces the diversity of custom hardware solutions in favour of software.

  18. Discrete event simulation of the ATLAS second level trigger

    International Nuclear Information System (INIS)

    Vermeulen, J.C.; Dankers, R.J.; Hunt, S.; Harris, F.; Hortnagl, C.; Erasov, A.; Bogaerts, A.

    1998-01-01

    Discrete event simulation is applied for determining the computing and networking resources needed for the ATLAS second level trigger. This paper discusses the techniques used and some of the results obtained so far for well defined laboratory configurations and for the full system

  19. Identification of Hadronic Tau Lepton Decays at the ATLAS Detector Using Artificial Neural Networks

    CERN Document Server

    AUTHOR|(CDS)2093068; Zuber, Kai

    Tau leptons play an important role in a wide range of physics analyses at the LHC, such as the verification of the Standard Model at the TeV scale or the determination of Higgs boson properties. For the identification of hadronically decaying tau leptons with the ATLAS detector, a sophisticated, multi-variate algorithm is required. This is due to the high production cross section for QCD jets, the dominant background. Artificial neural networks (ANNs) have gained much attention in recent years by winning several pattern recognition contests. In this thesis, a survey of ANNs is given with a focus on developments of the past 20 years. Based on this work, a novel, ANN-based tau identification is presented which is competitive to the current BDT-based approach. The influence of various hyperparameters on the identification is studied and optimized. Both stability and performance are enhanced through formation of ANN ensembles. Additionally, a score-flattening algorithm is presented that is beneficial to physics a...

  20. The ATLAS Computing Agora: a resource web site for citizen science projects

    CERN Document Server

    Bourdarios, Claire; The ATLAS collaboration

    2016-01-01

    The ATLAS collaboration has recently setup a number of citizen science projects which have a strong IT component and could not have been envisaged without the growth of general public computing resources and network connectivity: event simulation through volunteer computing, algorithms improvement via Machine Learning challenges, event display analysis on citizen science platforms, use of open data, etc. Most of the interactions with volunteers are handled through message boards, but specific outreach material was also developed, giving an enhanced visibility to the ATLAS software and computing techniques, challenges and community. In this talk the Atlas Computing Agora (ACA) web platform will be presented as well as some of the specific material developed for some of the projects.

  1. Evolution of the ReadOut System of the ATLAS experiment

    CERN Document Server

    Borga, A; The ATLAS collaboration; Joos, M; Schumacher, J; Tremblet, L; Vandelli, W; Vermeulen, J; Werner, P; Wickens, F

    2014-01-01

    The ReadOut System (ROS) is a central and essential part of the ATLAS data-acquisition system. It receives and buffers event data accepted from all sub-detectors and first-level trigger subsystems. Event data are subsequently forwarded to the High-Level Trigger system and Event Builder via a GbE-based network. The ATLAS ROS will be completely renewed in view of the demanding conditions expected during LHC Run 2 and Run 3. The new ROS will consist of roughly 100 Linux-based 2U-high rack-mounted server PCs, each equipped with 2 PCIe I/O cards and four 10GbE interfaces. The FPGA-based PCIe I/O cards, developed by the ALICE collaboration, will be configured with ATLAS-specific firmware, called RobinNP. They will provide connectivity to about 2000 point-to-point optical links conveying the ATLAS event data. This dense configuration provides an excellent test bench for studying I/O efficiency and challenges in current COTS PC architectures with non-uniform memory and I/O access paths. In this paper the requirements...

  2. Evolution of the ReadOut System of the ATLAS experiment

    CERN Document Server

    Borga, A; The ATLAS collaboration; Green, B; Kugel, A; Joos, M; Panduro Vazquez, W; Schumacher, J; Teixeira-Dias, P; Tremblet, L; Vandelli, W; Vermeulen, J; Werner, P; Wickens, F

    2014-01-01

    The ReadOut System (ROS) is a central and essential part of the ATLAS DAQ system. It receives and buffers data of events accepted by the first-level trigger from all subdetectors and first-level trigger subsystems. Event data are subsequently forwarded to the High-Level Trigger system and Event Builder via a 1 GbE-based network. The ATLAS ROS is completely renewed in view of the demanding conditions expected during LHC Run 2 and Run 3, to replace obsolete technologies and space constraints require it to be compact. The new ROS will consist of roughly 100 Linux-based 2U high rack mounted server PCs, each equipped with 2 PCIe I/O cards and two four 10 GbE interfaces. The FPGA-based PCIe I/O cards, developed by the ALICE collaboration, will be configured with ATLAS-specific firmware, the so-called RobinNP firmware. They will provide the connectivity to about 2000 optical point-to-point links conveying the ATLAS event data. This dense configuration provides an excellent test bench for studying I/O efficiency and ...

  3. Advances in ATLAS@Home towards a major ATLAS computing resource

    CERN Document Server

    Cameron, David; The ATLAS collaboration

    2018-01-01

    The volunteer computing project ATLAS@Home has been providing a stable computing resource for the ATLAS experiment since 2013. It has recently undergone some significant developments and as a result has become one of the largest resources contributing to ATLAS computing, by expanding its scope beyond traditional volunteers and into exploitation of idle computing power in ATLAS data centres. Removing the need for virtualization on Linux and instead using container technology has made the entry barrier significantly lower data centre participation and in this paper, we describe the implementation and results of this change. We also present other recent changes and improvements in the project. In early 2017 the ATLAS@Home project was merged into a combined LHC@Home platform, providing a unified gateway to all CERN-related volunteer computing projects. The ATLAS Event Service shifts data processing from file-level to event-level and we describe how ATLAS@Home was incorporated into this new paradigm. The finishing...

  4. A Prototype Ontology Tool and Interface for Coastal Atlas Interoperability

    Science.gov (United States)

    Wright, D. J.; Bermudez, L.; O'Dea, L.; Haddad, T.; Cummins, V.

    2007-12-01

    Atlas Network (ICAN). Lessons learned from this prototype will help build regional atlases and improve decision support systems.

  5. The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation

    International Nuclear Information System (INIS)

    Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

    2015-01-01

    The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy

  6. ATLAS Overview Week at Brookhaven

    CERN Multimedia

    Pilcher, J

    Over 200 ATLAS participants gathered at Brookhaven National Laboratory during the first week of June for our annual overview week. Some system communities arrived early and held meetings on Saturday and Sunday, and the detector interface group (DIG) and Technical Coordination also took advantage of the time to discuss issues of interest for all detector systems. Sunday was also marked by a workshop on the possibilities for heavy ion physics with ATLAS. Beginning on Monday, and for the rest of the week, sessions were held in common in the well equipped Berkner Hall auditorium complex. Laptop computers became the norm for presentations and a wireless network kept laptop owners well connected. Most lunches and dinners were held on the lawn outside Berkner Hall. The weather was very cooperative and it was an extremely pleasant setting. This picture shows most of the participants from a view on the roof of Berkner Hall. Technical Coordination and Integration issues started the reports on Monday and became a...

  7. ATLAS Distributed Computing Experience and Performance During the LHC Run-2

    Science.gov (United States)

    Filipčič, A.; ATLAS Collaboration

    2017-10-01

    ATLAS Distributed Computing during LHC Run-1 was challenged by steadily increasing computing, storage and network requirements. In addition, the complexity of processing task workflows and their associated data management requirements led to a new paradigm in the ATLAS computing model for Run-2, accompanied by extensive evolution and redesign of the workflow and data management systems. The new systems were put into production at the end of 2014, and gained robustness and maturity during 2015 data taking. ProdSys2, the new request and task interface; JEDI, the dynamic job execution engine developed as an extension to PanDA; and Rucio, the new data management system, form the core of Run-2 ATLAS distributed computing engine. One of the big changes for Run-2 was the adoption of the Derivation Framework, which moves the chaotic CPU and data intensive part of the user analysis into the centrally organized train production, delivering derived AOD datasets to user groups for final analysis. The effectiveness of the new model was demonstrated through the delivery of analysis datasets to users just one week after data taking, by completing the calibration loop, Tier-0 processing and train production steps promptly. The great flexibility of the new system also makes it possible to execute part of the Tier-0 processing on the grid when Tier-0 resources experience a backlog during high data-taking periods. The introduction of the data lifetime model, where each dataset is assigned a finite lifetime (with extensions possible for frequently accessed data), was made possible by Rucio. Thanks to this the storage crises experienced in Run-1 have not reappeared during Run-2. In addition, the distinction between Tier-1 and Tier-2 disk storage, now largely artificial given the quality of Tier-2 resources and their networking, has been removed through the introduction of dynamic ATLAS clouds that group the storage endpoint nucleus and its close-by execution satellite sites. All stable

  8. ATLAS Outreach Highlights

    CERN Document Server

    Cheatham, Susan; The ATLAS collaboration

    2016-01-01

    The ATLAS outreach team is very active, promoting particle physics to a broad range of audiences including physicists, general public, policy makers, students and teachers, and media. A selection of current outreach activities and new projects will be presented. Recent highlights include the new ATLAS public website and ATLAS Open Data, the very recent public release of 1 fb-1 of ATLAS data.

  9. ALICE common read-out receiver card status and HLT implementation

    Energy Technology Data Exchange (ETDEWEB)

    Engel, Heiko; Kebschull, Udo [IRI, Goethe-Universitaet Frankfurt am Main (Germany); Collaboration: ALICE-Collaboration

    2015-07-01

    The ALICE Common Read-Out Receiver Card (C-RORC) is an FPGA based PCIe read out board with optical interfaces primarily developed to replace the previous ALICE High-Level Trigger (HLT) and Data Acquisition (DAQ) Read-Out Receiver Cards from Run1 with a state of the art hardware platform to cope with the increased link rates and event data volume of Run2. The large scale production of the C-RORCs for Run2 has been completed in cooperation with ATLAS and the boards are installed in the productive clusters of ALICE HLT, ALICE DAQ and ATLAS TDAQ ROS. This contribution describes the hardware and firmware of the C-RORC in the ALICE HLT application and its online processing capabilities. Additionally, a high level dataflow description approach to implement hardware processing steps more efficiently is presented.

  10. CERN Open Days 2013, Point 1 - ATLAS: ATLAS Experiment

    CERN Multimedia

    CERN Photolab

    2013-01-01

    Stand description: The ATLAS Experiment at CERN is one of the largest and most complex scientific endeavours ever assembled. The detector, located at collision point 1 of the LHC, is designed to explore the fundamental components of nature and to study the forces that shape our universe. The past year’s discovery of a Higgs boson is one of the most important scientific achievements of our time, yet this is only one of many key goals of ATLAS. During a brief break in their journey, some of the 3000-member ATLAS collaboration will be taking time to share the excitement of this exploration with you. On surface no restricted access  The exhibit at Point 1 will give visitors a chance to meet these modern-day explorers and to learn from them how answers to the most fundamental questions of mankind are being sought. Activities will include a visit to the ATLAS detector, located 80m below ground; watching the prize-winning ATLAS movie in the ATLAS cinema; seeing real particle tracks in a cloud chamber and discussi...

  11. The 3rd ATLAS Domestic Standard Problem for Improvement of Safety Analysis Technology

    International Nuclear Information System (INIS)

    Choi, Ki-Yong; Kang, Kyoung-Ho; Park, Yusun; Kim, Jongrok; Bae, Byoung-Uhn; Choi, Nam-Hyun

    2014-01-01

    The third ATLAS DSP (domestic standard problem exercise) was launched at the end of 2012 in response to the strong need for continuation of the ATLAS DSP. A guillotine break of a main steam line without LOOP at a zero power condition was selected as a target scenario, and it was successfully completed in the beginning of 2014. In the 3 rd ATLAS DSP, comprehensive utilization of the integral effect test data was made by dividing analysis with three topics; 1. scale-up where extrapolation of ATLAS IET data was investigated 2. 3D analysis where how much improvement can be obtained by 3D modeling was studied 3. 1D sensitivity analysis where the key phenomena affecting the SLB simulation were identified and the best modeling guideline was achieved. Through such DSP exercises, it has been possible to effectively utilize high-quality ATLAS experimental data of to enhance thermal-hydraulic understanding and to validate the safety analysis codes. A strong human network and technical expertise sharing among the various nuclear experts are also important outcomes from this program

  12. Evolution of the ATLAS data and computing model for a Tier2 in the EGI infrastructure

    CERN Document Server

    Fernández Casaní, A; The ATLAS collaboration; González de la Hoz, S; Salt Cairols, J; Fassi, F; Kaci, M; Lamas, A; Oliver, E; Sánchez, J; Sánchez, V

    2012-01-01

    Since the start of the LHC pp collisions in 2010, the ATLAS computing model has moved from a more strict design, where every Tier2 had a liaison and a network dependence from a Tier1, to a more meshed approach where every cloud could be connected. Evolution of ATLAS data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. It also requires rethinking the network infrastructure to enable any Tier2 and associated Tier3 to easily connect to any Tier1 or Tier2. Tier2s are becoming more and more important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used more efficiently. In this way Tier1s and Tier2s are becoming more equivalent for t...

  13. Benefits and performance of ATLAS approaches to utilizing opportunistic resources

    CERN Document Server

    Filip\\v{c}i\\v{c}, Andrej; The ATLAS collaboration

    2016-01-01

    ATLAS has been extensively exploring possibilities of using computing resources extending beyond conventional grid sites in the WLCG fabric to deliver as many computing cycles as possible and thereby enhance the significance of the Monte-Carlo samples to deliver better physics results. The difficulties of using such opportunistic resources come from architectural differences such as unavailability of grid services, the absence of network connectivity on worker nodes or inability to use standard authorization protocols. Nevertheless, ATLAS has been extremely successful in running production payloads on a variety of sites, thanks largely to the job execution workflow design in which the job assignment, input data provisioning and execution steps are clearly separated and can be offloaded to custom services. To transparently include the opportunistic sites in the ATLAS central production system, several models with supporting services have been developed to mimic the functionality of a full WLCG site. Some are e...

  14. An extensive assessment of network alignment algorithms for comparison of brain connectomes.

    Science.gov (United States)

    Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario

    2017-06-06

    Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.

  15. Danish heat atlas as a support tool for energy system models

    International Nuclear Information System (INIS)

    Petrovic, Stefan N.; Karlsson, Kenneth B.

    2014-01-01

    Highlights: • The GIS method for calculating costs of district heating expansion is presented. • High socio-economic potential for district heating is identified within urban areas. • The method for coupling a heat atlas and TIMES optimization model is proposed. • Presented methods can be used for any geographical region worldwide. - Abstract: In the past four decades following the global oil crisis in 1973, Denmark has implemented remarkable changes in its energy sector, mainly due to the energy conservation measures on the demand side and the energy efficiency improvements on the supply side. Nowadays, the capital intensive infrastructure investments, such as the expansion of district heating networks and the introduction of significant heat saving measures require highly detailed decision-support tool. A Danish heat atlas provides highly detailed database with extensive information about more than 2.5 million buildings in Denmark. Energy system analysis tools incorporate environmental, economic, energy and engineering analysis of future energy systems and are considered crucial for the quantitative assessment of transitional scenarios towards future milestones, such as EU 2020 goals and Denmark’s goal of achieving fossil free society after 2050. The present paper shows how a Danish heat atlas can be used for providing inputs to energy system models, especially related to the analysis of heat saving measures within building stock and expansion of district heating networks. As a result, marginal cost curves are created, approximated and prepared for the use in optimization energy system model. Moreover, it is concluded that heat atlas can contribute as a tool for data storage and visualisation of results

  16. Image File - TP Atlas | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available ption of data contents Network diagrams (in PNG format) for each project. One project has one pathway file o...List Contact us TP Atlas Image File Data detail Data name Image File DOI 10.18908/lsdba.nbdc01161-004 Descri

  17. Study of an on-line filtering system for the ATLAS detector

    International Nuclear Information System (INIS)

    Fede, E.

    2001-01-01

    The first chapter presents today's knowledge about particle physics and a description of the main decay channels and physical signatures associated to the Higgs boson is given. The second chapter is dedicated to the LHC accelerator with a focus on the ATLAS detector and its sub-detectors. The third chapter presents ATLAS triggering system and its data acquisition system. In the fourth chapter the functionalities required for an adequate event filtering system concerning physics issues and data managing are described. The design of a prototype based on a fleet of PC computers linked through an Ethernet network is presented in the fifth chapter

  18. ATLAS Thesis Award 2017

    CERN Multimedia

    Anthony, Katarina

    2018-01-01

    Winners of the ATLAS Thesis Award were presented with certificates and glass cubes during a ceremony on 22 February, 2018. They are pictured here with Karl Jakobs (ATLAS Spokesperson), Max Klein (ATLAS Collaboration Board Chair) and Katsuo Tokushuku (ATLAS Collaboration Board Deputy Chair).

  19. Virtual Machine Logbook - Enabling virtualization for ATLAS

    International Nuclear Information System (INIS)

    Yao Yushu; Calafiura, Paolo; Leggett, Charles; Poffet, Julien; Cavalli, Andrea; Frederic, Bapst

    2010-01-01

    ATLAS software has been developed mostly on CERN linux cluster lxplus or on similar facilities at the experiment Tier 1 centers. The fast rise of virtualization technology has the potential to change this model, turning every laptop or desktop into an ATLAS analysis platform. In the context of the CernVM project we are developing a suite of tools and CernVM plug-in extensions to promote the use of virtualization for ATLAS analysis and software development. The Virtual Machine Logbook (VML), in particular, is an application to organize work of physicists on multiple projects, logging their progress, and speeding up ''context switches'' from one project to another. An important feature of VML is the ability to share with a single 'click' the status of a given project with other colleagues. VML builds upon the save and restore capabilities of mainstream virtualization software like VMware, and provides a technology-independent client interface to them. A lot of emphasis in the design and implementation has gone into optimizing the save and restore process to makepractical to store many VML entries on a typical laptop disk or to share a VML entry over the network. At the same time, taking advantage of CernVM's plugin capabilities, we are extending the CernVM platform to help increase the usability of ATLAS software. For example, we added the ability to start the ATLAS event display on any computer running CernVM simply by clicking a button in a web browser. We want to integrate seamlessly VML with CernVM unique file system design to distribute efficiently ATLAS software on every physicist computer. The CernVM File System (CVMFS) download files on-demand via HTTP, and cache it locally for future use. This reduces by one order of magnitude the download sizes, making practical for a developer to work with multiple software releases on a virtual machine.

  20. ATLAS

    CERN Multimedia

    Akhnazarov, V; Canepa, A; Bremer, J; Burckhart, H; Cattai, A; Voss, R; Hervas, L; Kaplon, J; Nessi, M; Werner, P; Ten kate, H; Tyrvainen, H; Vandelli, W; Krasznahorkay, A; Gray, H; Alvarez gonzalez, B; Eifert, T F; Rolando, G; Oide, H; Barak, L; Glatzer, J; Backhaus, M; Schaefer, D M; Maciejewski, J P; Milic, A; Jin, S; Von torne, E; Limbach, C; Medinnis, M J; Gregor, I; Levonian, S; Schmitt, S; Waananen, A; Monnier, E; Muanza, S G; Pralavorio, P; Talby, M; Tiouchichine, E; Tocut, V M; Rybkin, G; Wang, S; Lacour, D; Laforge, B; Ocariz, J H; Bertoli, W; Malaescu, B; Sbarra, C; Yamamoto, A; Sasaki, O; Koriki, T; Hara, K; Da silva gomes, A; Carvalho maneira, J; Marcalo da palma, A; Chekulaev, S; Tikhomirov, V; Snesarev, A; Buzykaev, A; Maslennikov, A; Peleganchuk, S; Sukharev, A; Kaplan, B E; Swiatlowski, M J; Nef, P D; Schnoor, U; Oakham, G F; Ueno, R; Orr, R S; Abouzeid, O; Haug, S; Peng, H; Kus, V; Vitek, M; Temming, K K; Dang, N P; Meier, K; Schultz-coulon, H; Geisler, M P; Sander, H; Schaefer, U; Ellinghaus, F; Rieke, S; Nussbaumer, A; Liu, Y; Richter, R; Kortner, S; Fernandez-bosman, M; Ullan comes, M; Espinal curull, J; Chiriotti alvarez, S; Caubet serrabou, M; Valladolid gallego, E; Kaci, M; Carrasco vela, N; Lancon, E C; Besson, N E; Gautard, V; Bracinik, J; Bartsch, V C; Potter, C J; Lester, C G; Moeller, V A; Rosten, J; Crooks, D; Mathieson, K; Houston, S C; Wright, M; Jones, T W; Harris, O B; Byatt, T J; Dobson, E; Hodgson, P; Hodgkinson, M C; Dris, M; Karakostas, K; Ntekas, K; Oren, D; Duchovni, E; Etzion, E; Oren, Y; Ferrer, L M; Testa, M; Doria, A; Merola, L; Sekhniaidze, G; Giordano, R; Ricciardi, S; Milazzo, A; Falciano, S; De pedis, D; Dionisi, C; Veneziano, S; Cardarelli, R; Verzegnassi, C; Soualah, R; Ochi, A; Ohshima, T; Kishiki, S; Linde, F L; Vreeswijk, M; Werneke, P; Muijs, A; Vankov, P H; Jansweijer, P P M; Dale, O; Lund, E; Bruckman de renstrom, P; Dabrowski, W; Adamek, J D; Wolters, H; Micu, L; Pantea, D; Tudorache, V; Mjoernmark, J; Klimek, P J; Ferrari, A; Abdinov, O; Akhoundov, A; Hashimov, R; Shelkov, G; Khubua, J; Ladygin, E; Lazarev, A; Glagolev, V; Dedovich, D; Lykasov, G; Zhemchugov, A; Zolnikov, Y; Ryabenko, M; Sivoklokov, S; Vasilyev, I; Shalimov, A; Lobanov, M; Paramoshkina, E; Mosidze, M; Bingul, A; Nodulman, L J; Guarino, V J; Yoshida, R; Drake, G R; Calafiura, P; Haber, C; Quarrie, D R; Alonso, J R; Anderson, C; Evans, H; Lammers, S W; Baubock, M; Anderson, K; Petti, R; Suhr, C A; Linnemann, J T; Richards, R A; Tollefson, K A; Holzbauer, J L; Stoker, D P; Pier, S; Nelson, A J; Isakov, V; Martin, A J; Adelman, J A; Paganini, M; Gutierrez, P; Snow, J M; Pearson, B L; Cleland, W E; Savinov, V; Wong, W; Goodson, J J; Li, H; Lacey, R A; Gordeev, A; Gordon, H; Lanni, F; Nevski, P; Rescia, S; Kierstead, J A; Liu, Z; Yu, W W H; Bensinger, J; Hashemi, K S; Bogavac, D; Cindro, V; Hoeferkamp, M R; Coelli, S; Iodice, M; Piegaia, R N; Alonso, F; Wahlberg, H P; Barberio, E L; Limosani, A; Rodd, N L; Jennens, D T; Hill, E C; Pospisil, S; 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Chekanov, S; Le compte, T J; Love, J R; Ciocio, A; Hinchliffe, I; Tsulaia, V; Gomez, A; Luehring, F; Zieminska, D; Huth, J E; Gonski, J L; Oreglia, M; Tang, F; Shochet, M J; Costin, T; Mcleod, A; Uzunyan, S; Martin, S P; Pope, B G; Schwienhorst, R H; Brau, J E; Ptacek, E S; Milburn, R H; Sabancilar, E; Lauer, R; Saleem, M; Mohamed meera lebbai, M R; Lou, X; Reeves, K B; Rijssenbeek, M; Novakova, P N; Rahm, D; Steinberg, P A; Wenaus, T J; Paige, F; Ye, S; Kotcher, J R; Assamagan, K A; Oliveira damazio, D; Maeno, T; Henry, A; Dushkin, A; Costa, G; Meroni, C; Resconi, S; Lari, T; Biglietti, M; Lohse, T; Gonzalez silva, M L; Monticelli, F G; Saavedra, A F; Patel, N D; Ciodaro xavier, T; Asevedo nepomuceno, A; Lefebvre, M; Albert, J E; Kubik, P; Faltova, J; Turecek, D; Solc, J; Schaile, O; Ebke, J; Losel, P J; Zeitnitz, C; Sturm, P D; Barreiro alonso, F; Modesto alapont, P; Soret medel, J; Garzon alama, E J; Gee, C N; Mccubbin, N A; Sankey, D; Emeliyanov, D; Dewhurst, A L; Houlden, M A; Klein, M; 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Sadrozinski, H; Lockman, W S; Martinez-mc kinney, G; Goussiou, A; Jones, A; Lie, K; Hasegawa, Y; Olcese, M; Gilewsky, V; Harrison, P F; Janus, M; Spangenberg, M; De, K; Ozturk, N; Pal, A K; Darmora, S; Bullock, D J; Oviawe, O; Derkaoui, J E; Rahal, G; Sircar, A; Frey, A S; Stolte, P; Rosien, N; Zoch, K; Li, L; Schouten, D W; Catinaccio, A; Ciapetti, M; Delruelle, N; Ellis, N; Farthouat, P; Hoecker, A; Klioutchnikova, T; Macina, D; Malyukov, S; Spiwoks, R D; Unal, G P; Vandoni, G; Petersen, B A; Pommes, K; Nairz, A M; Wengler, T; Mladenov, D; Solans sanchez, C A; Lantzsch, K; Schmieden, K; Jakobsen, S; Ritsch, E; Sciuccati, A; Alves dos santos, A M; Ouyang, Q; Zhou, M; Brock, I C; Janssen, J; Katzy, J; Anders, C F; Nilsson, B S; Bazan, A; Di ciaccio, L; Yildizkaya, T; Collot, J; Malek, F; Trocme, B S; Breugnon, P; Godiot, S; Adam bourdarios, C; Coulon, J; Duflot, L; Petroff, P G; Zerwas, D; Lieuvin, M; Calderini, G; Laporte, D; Ocariz, J; Gabrielli, A; Ohska, T K; Kurochkin, Y; Kantserov, V; Vasilyeva, L; Speransky, M; Smirnov, S; Antonov, A; Bulekov, O; Tikhonov, Y; Sargsyan, L; Vardanyan, G; Budick, B; Kocian, M L; Luitz, S; Young, C C; Grenier, P J; Kelsey, M; Black, J E; Kneringer, E; Jussel, P; Horton, A J; Beaudry, J; Chandra, A; Ereditato, A; Topfel, C M; Mathieu, R; Bucci, F; Muenstermann, D; White, R M; He, M; Urban, J; Straka, M; Vrba, V; Schumacher, M; Parzefall, U; Mahboubi, K; Sommer, P O; Koepke, L H; Bethke, S; Moser, H; Wiesmann, M; Walkowiak, W A; Fleck, I J; Martinez-perez, M; Sanchez sanchez, C A; Jorgensen roca, S; Accion garcia, E; Sainz ruiz, C A; Valls ferrer, J A; Amoros vicente, G; Vives torrescasana, R; Ouraou, A; Formica, A; Hassani, S; Watson, M F; Cottin buracchio, G F; Bussey, P J; Saxon, D; Ferrando, J E; Collins-tooth, C L; Hall, D C; Cuhadar donszelmann, T; Dawson, I; Duxfield, R; Argyropoulos, T; Brodet, E; Livneh, R; Shougaev, K; Reinherz, E I; Guttman, N; Beretta, M M; Vilucchi, E; Aloisio, A; Patricelli, S; Caprio, M; Cevenini, F; De vecchi, C; Livan, M; Rimoldi, A; Vercesi, V; Ayad, R; Mastroberardino, A; Ciapetti, G; Luminari, L; Rescigno, M; Santonico, R; Salamon, A; Del papa, C; Kurashige, H; Homma, Y; Tomoto, M; Horii, Y; Sugaya, Y; Hanagaki, K; Bobbink, G; Kluit, P M; Koffeman, E N; Van eijk, B; Lee, H; Eigen, G; Dorholt, O; Strandlie, A; Strzempek, P B; Dita, S; Stoicea, G; Chitan, A; Leven, S S; Moa, T; Brenner, R; Ekelof, T J C; Olshevskiy, A; Roumiantsev, V; Chlachidze, G; Zimine, N; Gusakov, Y; Grigalashvili, N; Mineev, M; Potrap, I; Barashkou, A; Shoukavy, D; Shaykhatdenov, B; Pikelner, A; Gladilin, L; Ammosov, V; Abramov, A; Arik, M; Sahinsoy, M; Uysal, Z; Azizi, K; Hotinli, S C; Zhou, S; Berger, E; Blair, R; Underwood, D G; Einsweiler, K; Garcia-sciveres, M A; Siegrist, J L; Kipnis, I; Dahl, O; Holland, S; Barbaro galtieri, A; Smith, P T; Parua, N; Franklin, M; Mercurio, K M; Tong, B; Pod, E; Cole, S G; Hopkins, W H; Guest, D H; Severini, H; Marsicano, J J; Abbott, B K; Wang, Q; Lissauer, D; Ma, H; Takai, H; Rajagopalan, S; Protopopescu, S D; Snyder, S S; Undrus, A; Popescu, R N; Begel, M A; Blocker, C A; Amelung, C; Mandic, I; Macek, B; Tucker, B H; Citterio, M; Troncon, C; Orestano, D; Taccini, C; Romeo, G L; Dova, M T; Taylor, G N; Gesualdi manhaes, A; Mcpherson, R A; Sobie, R; Taylor, R P; Dolezal, Z; Kodys, P; Slovak, R; Sopko, B; Vacek, V; Sanders, M P; Hertenberger, R; Meineck, C; Becks, K; Kind, P; Sandhoff, M; Cantero garcia, J; De la torre perez, H; Castillo gimenez, V; Ros, E; Hernandez jimenez, Y; Chadelas, R; Santoni, C; Washbrook, A J; O'brien, B J; Wynne, B M; Mehta, A; Vossebeld, J H; Landon, M; Teixeira dias castanheira, M; Cerrito, L; Keates, J R; Fassouliotis, D; Chardalas, M; Manousos, A; Grachev, V; Seliverstov, D; Sedykh, E; Cakir, O; Ciftci, R; Edson, W; Prell, S A; Rosati, M; Stroman, T; Jiang, H; Neal, H A; Li, X; Gan, K K; Smith, D S; Kruse, M C; Ko, B R; Leung fook cheong, A M; Cole, B; Angerami, A R; Greene, Z S; Kroll, J I; Van berg, R P; Forbush, D A; Lubatti, H; Raisher, J; Shupe, M A; Wolin, S; Oshita, H; Gaudio, G; Das, R; Konig, A C; Croft, V A; Harvey, A; Maaroufi, F; Melo, I; Greenwood jr, Z D; Shabalina, E; Mchedlidze, G; Drechsler, E; Rieger, J K; Blackston, M; Colombo, T

    2002-01-01

    % ATLAS \\\\ \\\\ ATLAS is a general-purpose experiment for recording proton-proton collisions at LHC. The ATLAS collaboration consists of 144 participating institutions (June 1998) with more than 1750~physicists and engineers (700 from non-Member States). The detector design has been optimized to cover the largest possible range of LHC physics: searches for Higgs bosons and alternative schemes for the spontaneous symmetry-breaking mechanism; searches for supersymmetric particles, new gauge bosons, leptoquarks, and quark and lepton compositeness indicating extensions to the Standard Model and new physics beyond it; studies of the origin of CP violation via high-precision measurements of CP-violating B-decays; high-precision measurements of the third quark family such as the top-quark mass and decay properties, rare decays of B-hadrons, spectroscopy of rare B-hadrons, and $ B ^0 _{s} $-mixing. \\\\ \\\\The ATLAS dectector, shown in the Figure includes an inner tracking detector inside a 2~T~solenoid providing an axial...

  1. Supporting ATLAS

    CERN Multimedia

    2003-01-01

    Eighteen feet made of stainless steel will support the barrel ATLAS detector in the cavern at Point 1. In total, the ATLAS feet system will carry approximately 6000 tons, and will give the same inclination to the detector as the LHC accelerator. The installation of the feet is scheduled to finish during January 2004 with an installation precision at the 1 mm level despite their height of 5.3 metres. The manufacture was carried out in Russia (Company Izhorskiye Zavody in St. Petersburg), as part of a Russian and JINR Dubna in-kind contribution to ATLAS. Involved in the installation is a team from IHEP-Protvino (Russia), the ATLAS technical co-ordination team at CERN, and the CERN survey team. In all, about 15 people are involved. After the feet are in place, the barrel toroid magnet and the barrel calorimeters will be installed. This will keep the ATLAS team busy for the entire year 2004.

  2. Quark vs Gluon Jet Tagging at ATLAS

    CERN Document Server

    Rubbo, Francesco; The ATLAS collaboration

    2017-01-01

    Distinguishing quark-initiated from gluon-initiated jets is useful for many measurements and searches at the LHC. We present a quark-initiated versus gluon-initiated jet tagger from the ATLAS experiment using the number of reconstructed charged particles inside the jet. The measurement of the charged-particle multiplicity inside jets from Run 1 is used to derive uncertainties on the tagger performance for Run 2. With an efficiency of 60% to select quark-initiated jets, the efficiency to select gluon-initiated jets is between 10 and 20% across a wide range in jet pT up to 1.5 TeV with about an absolute 5% systematic uncertainty on the efficiencies. In addition, we also present preliminary studies on a tagger for the ATLAS experiment using the full radiation pattern inside a jet processed as images in deep neural network classifiers.

  3. Rudolf Böck (1935 - 2015)

    CERN Multimedia

    2015-01-01

    Rudolf Böck, a distinguished scientist who worked at CERN for over 40 years, died unexpectedly on 15 April at the age of 80.   Rudy obtained his PhD in Munich and started work at CERN on 5 October 1959, just a few years after its establishment, as a mathematician in the Data Handling Division. He worked on a series of experiments including WA7, UA1, and JETSET at LEAR, as well as leading the RD11 (EAST) project studying second-level triggering for the LHC experiments, before joining ATLAS.   As a member of the ATLAS TDAQ team, Rudy was deeply engaged in second-level trigger activities – from the physics requirements and architectural design to studies with early prototypes. He retired from CERN in 2000, ending his activity on ATLAS, but joined the MAGIC experiment in La Palma as a member of the MPI Munich group, splitting his time between Munich and Geneva. Rudy will be remembered as a charming, kind and generous man, always interested and ready to share his wisd...

  4. The LVL2 trigger goes online

    CERN Multimedia

    David Berge

    On Friday, the 9th of February, the ATLAS TDAQ community reached an important milestone. In a successful integration test, cosmic-ray muons were recorded with parts of the muon spectrometer, the central-trigger system and a second-level trigger algorithm. This was actually the first time that a full trigger slice all the way from the first-level trigger muon chambers up to event building after event selection by the second-level trigger ran online with cosmic rays. The ATLAS trigger and data acquisition system has a three-tier structure that is designed to cope with the enormous demands of proton-proton collisions at a bunch-crossing frequency of 40 MHz, with a typical event size of 1-2 MB. The online event selection has to reduce the incoming rate by a factor of roughly 200,000 to 200 Hz, a rate digestible by the archival-storage and offline-processing facilities. ATLAS has a mixed system: the first-level trigger (LVL1) is in hardware, while the other two consecutive levels, the second-level trigger (LVL2)...

  5. Integration of the Chinese HPC Grid in ATLAS Distributed Computing

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160; The ATLAS collaboration

    2016-01-01

    Fifteen Chinese High Performance Computing sites, many of them on the TOP500 list of most powerful supercomputers, are integrated into a common infrastructure providing coherent access to a user through an interface based on a RESTful interface called SCEAPI. These resources have been integrated into the ATLAS Grid production system using a bridge between ATLAS and SCEAPI which translates the authorization and job submission protocols between the two environments. The ARC Computing Element (ARC CE) forms the bridge using an extended batch system interface to allow job submission to SCEAPI. The ARC CE was setup at the Institute for High Energy Physics, Beijing, in order to be as close as possible to the SCEAPI front-end interface at the Computing Network Information Center, also in Beijing. This paper describes the technical details of the integration between ARC CE and SCEAPI and presents results so far with two supercomputer centers, Tianhe-IA and ERA. These two centers have been the pilots for ATLAS Monte C...

  6. Integration of the Chinese HPC Grid in ATLAS Distributed Computing

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160

    2017-01-01

    Fifteen Chinese High-Performance Computing sites, many of them on the TOP500 list of most powerful supercomputers, are integrated into a common infrastructure providing coherent access to a user through an interface based on a RESTful interface called SCEAPI. These resources have been integrated into the ATLAS Grid production system using a bridge between ATLAS and SCEAPI which translates the authorization and job submission protocols between the two environments. The ARC Computing Element (ARC-CE) forms the bridge using an extended batch system interface to allow job submission to SCEAPI. The ARC-CE was setup at the Institute for High Energy Physics, Beijing, in order to be as close as possible to the SCEAPI front-end interface at the Computing Network Information Center, also in Beijing. This paper describes the technical details of the integration between ARC-CE and SCEAPI and presents results so far with two supercomputer centers, Tianhe-IA and ERA. These two centers have been the pilots for ATLAS Monte C...

  7. Global Data Grid Efforts for ATLAS

    CERN Multimedia

    Gardner, R.

    2001-01-01

    Over the past two years computational data grids have emerged as a promising new technology for large scale, data-intensive computing required by the LHC experiments, as outlined by the recent "Hoffman" review panel that addressed the LHC computing challenge. The problem essentially is to seamlessly link physicists to petabyte-scale data and computing resources, distributed worldwide, and connected by high-bandwidth research networks. Several new collaborative initiatives in Europe, the United States, and Asia have formed to address the problem. These projects are of great interest to ATLAS physicists and software developers since their objective is to offer tools that can be integrated into the core ATLAS application framework for distributed event reconstruction, Monte Carlo simulation, and data analysis, making it possible for individuals and groups of physicists to share information, data, and computing resources in new ways and at scales not previously attempted. In addition, much of the distributed IT...

  8. Probabilistic liver atlas construction.

    Science.gov (United States)

    Dura, Esther; Domingo, Juan; Ayala, Guillermo; Marti-Bonmati, Luis; Goceri, E

    2017-01-13

    Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.

  9. Report to users of ATLAS

    International Nuclear Information System (INIS)

    Ahmad, I.; Glagola, B.

    1995-05-01

    This report contains discussing in the following areas: Status of the Atlas accelerator; highlights of recent research at Atlas; concept for an advanced exotic beam facility based on Atlas; program advisory committee; Atlas executive committee; and Atlas and ANL physics division on the world wide web

  10. ATLAS Distributed Computing Automation

    CERN Document Server

    Schovancova, J; The ATLAS collaboration; Borrego, C; Campana, S; Di Girolamo, A; Elmsheuser, J; Hejbal, J; Kouba, T; Legger, F; Magradze, E; Medrano Llamas, R; Negri, G; Rinaldi, L; Sciacca, G; Serfon, C; Van Der Ster, D C

    2012-01-01

    The ATLAS Experiment benefits from computing resources distributed worldwide at more than 100 WLCG sites. The ATLAS Grid sites provide over 100k CPU job slots, over 100 PB of storage space on disk or tape. Monitoring of status of such a complex infrastructure is essential. The ATLAS Grid infrastructure is monitored 24/7 by two teams of shifters distributed world-wide, by the ATLAS Distributed Computing experts, and by site administrators. In this paper we summarize automation efforts performed within the ATLAS Distributed Computing team in order to reduce manpower costs and improve the reliability of the system. Different aspects of the automation process are described: from the ATLAS Grid site topology provided by the ATLAS Grid Information System, via automatic site testing by the HammerCloud, to automatic exclusion from production or analysis activities.

  11. The ATLAS High Level Trigger Steering Framework and the Trigger 
Configuration System.

    CERN Document Server

    Pérez Cavalcanti, Tiago; The ATLAS collaboration

    2011-01-01

    The ATLAS High Level Trigger Steering Framework and the Trigger 
Configuration System.
 
The ATLAS detector system installed in the Large Hadron Collider (LHC) 
at CERN is designed to study proton-proton and nucleus-nucleus 
collisions with a maximum center of mass energy of 14 TeV at a bunch 
collision rate of 40MHz.  In March 2010 the four LHC experiments saw 
the first proton-proton collisions at 7 TeV. Still within the year a 
collision rate of nearly 10 MHz is expected. At ATLAS, events of 
potential interest for ATLAS physics are selected by a three-level 
trigger system, with a final recording rate of about 200 Hz. The first 
level (L1) is implemented in custom hardware; the two levels of 
the high level trigger (HLT) are software triggers, running on large 
farms of standard computers and network devices. 

Within the ATLAS physics program more than 500 trigger signatures are 
defined. The HLT tests each signature on each L1-accepted event; the 
test outcome is recor...

  12. Advanced Technology Lifecycle Analysis System (ATLAS)

    Science.gov (United States)

    O'Neil, Daniel A.; Mankins, John C.

    2004-01-01

    Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is

  13. The ATLAS High Level Trigger Steering Framework and the Trigger Configuration System.

    CERN Document Server

    Perez Cavalcanti, Tiago; The ATLAS collaboration

    2011-01-01

    The ATLAS detector system installed in the Large Hadron Collider (LHC) at CERN is designed to study proton-proton and nucleus-nucleus collisions with a maximum centre of mass energy of 14 TeV at a bunch collision rate of 40MHz. In March 2010 the four LHC experiments saw the first proton-proton collisions at 7 TeV. Still within the year a collision rate of nearly 10 MHz is expected. At ATLAS, events of potential interest for ATLAS physics are selected by a three-level trigger system, with a final recording rate of about 200 Hz. The first level (L1) is implemented in custom hardware; the two levels of the high level trigger (HLT) are software triggers, running on large farms of standard computers and network devices. Within the ATLAS physics program more than 500 trigger signatures are defined. The HLT tests each signature on each L1-accepted event; the test outcome is recorded for later analysis. The HLT-Steering is responsible for this. It foremost ensures the independent test of each signature, guarantying u...

  14. A high-resolution anatomical atlas of the transcriptome in the mouse embryo.

    Directory of Open Access Journals (Sweden)

    Graciana Diez-Roux

    Full Text Available Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org, consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease.

  15. EnviroAtlas - Percent Stream Buffer Zone As Natural Land Cover for the Conterminous United States

    Science.gov (United States)

    This EnviroAtlas dataset shows the percentage of land area within a 30 meter buffer zone along the National Hydrography Dataset (NHD) high resolution stream network, and along water bodies such as lakes and ponds that are connected via flow to the streams, that is classified as forest land cover, modified forest land cover, and natural land cover using the 2006 National Land Cover Dataset (NLCD) for each Watershed Boundary Dataset (WBD) 12-digit hydrological unit (HUC) in the conterminous United States. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  16. ATLAS-AWS

    International Nuclear Information System (INIS)

    Gehrcke, Jan-Philip; Stonjek, Stefan; Kluth, Stefan

    2010-01-01

    We show how the ATLAS offline software is ported on the Amazon Elastic Compute Cloud (EC2). We prepare an Amazon Machine Image (AMI) on the basis of the standard ATLAS platform Scientific Linux 4 (SL4). Then an instance of the SLC4 AMI is started on EC2 and we install and validate a recent release of the ATLAS offline software distribution kit. The installed software is archived as an image on the Amazon Simple Storage Service (S3) and can be quickly retrieved and connected to new SL4 AMI instances using the Amazon Elastic Block Store (EBS). ATLAS jobs can then configure against the release kit using the ATLAS configuration management tool (cmt) in the standard way. The output of jobs is exported to S3 before the SL4 AMI is terminated. Job status information is transferred to the Amazon SimpleDB service. The whole process of launching instances of our AMI, starting, monitoring and stopping jobs and retrieving job output from S3 is controlled from a client machine using python scripts implementing the Amazon EC2/S3 API via the boto library working together with small scripts embedded in the SL4 AMI. We report our experience with setting up and operating the system using standard ATLAS job transforms.

  17. EnviroAtlas

    Data.gov (United States)

    City and County of Durham, North Carolina — This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). The layers in this web...

  18. Software Development and Testing Approach and Challenges in a distributed HEP Collaboration

    CERN Document Server

    Burckhart-Chromek, Doris

    2007-01-01

    In developing the ATLAS [1] Trigger and Data Acquisition (TDAQ) software, the team is applying the iterative waterfall model, evolutionary process management, formal software inspection, and lightweight review techniques. The long preparation phase, with a geographically widespread development team required that the standard techniques be adapted to this HEP environment. The testing process is receiving special attention. Unit tests and check targets in nightly project builds form the basis for the subsequent software project release testing. The integrated software is then being run on computing farms that give further opportunites for gaining experience, fault finding, and acquiring ideas for improvement. Dedicated tests on a farm of up to 1000 nodes address the large-scale aspect of the project. Integration test activities on the experimental site include the special purpose-built event readout hardware. Deployment in detector commissioning starts the countdown towards running the final ATLAS experiment. T...

  19. Dear ATLAS colleagues,

    CERN Multimedia

    PH Department

    2008-01-01

    We are collecting old pairs of glasses to take out to Mali, where they can be re-used by people there. The price for a pair of glasses can often exceed 3 months salary, so they are prohibitively expensive for many people. If you have any old spectacles you can donate, please put them in the special box in the ATLAS secretariat, bldg.40-4-D01 before the Christmas closure on 19 December so we can take them with us when we leave for Africa at the end of the month. (more details in ATLAS e-news edition of 29 September 2008: http://atlas-service-enews.web.cern.ch/atlas-service-enews/news/news_mali.php) many thanks! Katharine Leney co-driver of the ATLAS car on the Charity Run to Mali

  20. Encoding atlases by randomized classification forests for efficient multi-atlas label propagation.

    Science.gov (United States)

    Zikic, D; Glocker, B; Criminisi, A

    2014-12-01

    We propose a method for multi-atlas label propagation (MALP) based on encoding the individual atlases by randomized classification forests. Most current approaches perform a non-linear registration between all atlases and the target image, followed by a sophisticated fusion scheme. While these approaches can achieve high accuracy, in general they do so at high computational cost. This might negatively affect the scalability to large databases and experimentation. To tackle this issue, we propose to use a small and deep classification forest to encode each atlas individually in reference to an aligned probabilistic atlas, resulting in an Atlas Forest (AF). Our classifier-based encoding differs from current MALP approaches, which represent each point in the atlas either directly as a single image/label value pair, or by a set of corresponding patches. At test time, each AF produces one probabilistic label estimate, and their fusion is done by averaging. Our scheme performs only one registration per target image, achieves good results with a simple fusion scheme, and allows for efficient experimentation. In contrast to standard forest schemes, in which each tree would be trained on all atlases, our approach retains the advantages of the standard MALP framework. The target-specific selection of atlases remains possible, and incorporation of new scans is straightforward without retraining. The evaluation on four different databases shows accuracy within the range of the state of the art at a significantly lower running time. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Recent ATLAS Articles on WLAP

    CERN Multimedia

    Goldfarb, S

    2005-01-01

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project is a system for the archiving and publishing of multimedia presentations, using the Web as medium. We list here newly available WLAP items relating to ATLAS: Atlas Software Week Plenary 6-10 December 2004 North American ATLAS Physics Workshop (Tucson) 20-21 December 2004 (17 talks) Physics Analysis Tools Tutorial (Tucson) 19 December 2004 Full Chain Tutorial 21 September 2004 ATLAS Plenary Sessions, 17-18 February 2005 (17 talks) Coming soon: ATLAS Tutorial on Electroweak Physics, 14 Feb. 2005 Software Workshop, 21-22 February 2005 Click here to browse WLAP for all ATLAS lectures.

  2. Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

    Science.gov (United States)

    Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

    2017-07-01

    Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. ATLAS people can run!

    CERN Multimedia

    Claudia Marcelloni de Oliveira; Pauline Gagnon

    It must be all the training we are getting every day, running around trying to get everything ready for the start of the LHC next year. This year, the ATLAS runners were in fine form and came in force. Nine ATLAS teams signed up for the 37th Annual CERN Relay Race with six runners per team. Under a blasting sun on Wednesday 23rd May 2007, each team covered the distances of 1000m, 800m, 800m, 500m, 500m and 300m taking the runners around the whole Meyrin site, hills included. A small reception took place in the ATLAS secretariat a week later to award the ATLAS Cup to the best ATLAS team. For the details on this complex calculation which takes into account the age of each runner, their gender and the color of their shoes, see the July 2006 issue of ATLAS e-news. The ATLAS Running Athena Team, the only all-women team enrolled this year, won the much coveted ATLAS Cup for the second year in a row. In fact, they are so good that Peter Schmid and Patrick Fassnacht are wondering about reducing the women's bonus in...

  4. A neural network clustering algorithm for the ATLAS silicon pixel detector

    Czech Academy of Sciences Publication Activity Database

    Aad, G.; Abbott, B.; Abdallah, J.; Böhm, Jan; Chudoba, Jiří; Havránek, Miroslav; Hejbal, Jiří; Jakoubek, Tomáš; Kepka, Oldřich; Kupčo, Alexander; Kůs, Vlastimil; Lokajíček, Miloš; Lysák, Roman; Marčišovský, Michal; Mikeštíková, Marcela; Myška, M.; Němeček, Stanislav; Šícho, Petr; Staroba, Pavel; Svatoš, Michal; Taševský, Marek; Vrba, Václav

    2014-01-01

    Roč. 9, Sep (2014), s. 1-38 ISSN 1748-0221 R&D Projects: GA MŠk(CZ) LG13009 Institutional support: RVO:68378271 Keywords : Monte Carlo * resolution * impact parameter * cluster * ATLAS * tracks * charged particle * CERN LHC Coll * longitudinal * transverse * splitting Subject RIV: BF - Elementary Particles and High Energy Physics Impact factor: 1.399, year: 2014

  5. Recent ATLAS Articles on WLAP

    CERN Multimedia

    J. Herr

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project is a system for the archiving and publishing of multimedia presentations, using the Web as medium. We list here newly available WLAP items relating to ATLAS: Atlas Physics Workshop 6-11 June 2005 June 2005 ATLAS Week Plenary Session Click here to browse WLAP for all ATLAS lectures.

  6. EnviroAtlas - Percent Stream Buffer Zone As Natural Land Cover for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset shows the percentage of land area within a 30 meter buffer zone along the National Hydrography Dataset (NHD) high resolution stream network,...

  7. New format for ATLAS e-news

    CERN Multimedia

    Pauline Gagnon

    ATLAS e-news got a new look! As of November 30, 2007, we have a new format for ATLAS e-news. Please go to: http://atlas-service-enews.web.cern.ch/atlas-service-enews/index.html . ATLAS e-news will now be published on a weekly basis. If you are not an ATLAS colaboration member but still want to know how the ATLAS experiment is doing, we will soon have a version of ATLAS e-news intended for the general public. Information will be sent out in due time.

  8. ATLAS Distributed Computing experience and performance during the LHC Run-2

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160; The ATLAS collaboration

    2017-01-01

    ATLAS Distributed Computing during LHC Run-1 was challenged by steadily increasing computing, storage and network requirements. In addition, the complexity of processing task workflows and their associated data management requirements led to a new paradigm in the ATLAS computing model for Run-2, accompanied by extensive evolution and redesign of the workflow and data management systems. The new systems were put into production at the end of 2014, and gained robustness and maturity during 2015 data taking. ProdSys2, the new request and task interface; JEDI, the dynamic job execution engine developed as an extension to PanDA; and Rucio, the new data management system, form the core of Run-2 ATLAS distributed computing engine. One of the big changes for Run-2 was the adoption of the Derivation Framework, which moves the chaotic CPU and data intensive part of the user analysis into the centrally organized train production, delivering derived AOD datasets to user groups for final analysis. The effectiveness of the...

  9. ATLAS Distributed Computing experience and performance during the LHC Run-2

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00081160; The ATLAS collaboration

    2016-01-01

    ATLAS Distributed Computing during LHC Run-1 was challenged by steadily increasing computing, storage and network requirements. In addition, the complexity of processing task workflows and their associated data management requirements led to a new paradigm in the ATLAS computing model for Run-2, accompanied by extensive evolution and redesign of the workflow and data management systems. The new systems were put into production at the end of 2014, and gained robustness and maturity during 2015 data taking. ProdSys2, the new request and task interface; JEDI, the dynamic job execution engine developed as an extension to PanDA; and Rucio, the new data management system, form the core of the Run-2 ATLAS distributed computing engine. One of the big changes for Run-2 was the adoption of the Derivation Framework, which moves the chaotic CPU and data intensive part of the user analysis into the centrally organized train production, delivering derived AOD datasets to user groups for final analysis. The effectiveness of...

  10. The North American Drought Atlas: Tree-Ring Reconstructions of Drought Variability for Climate Modeling and Assessment

    Science.gov (United States)

    Cook, E. R.

    2007-05-01

    The North American Drought Atlas describes a detailed reconstruction of drought variability from tree rings over most of North America for the past 500-1000 years. The first version of it, produced over three years ago, was based on a network of 835 tree-ring chronologies and a 286-point grid of instrumental Palmer Drought Severity Indices (PDSI). These gridded PDSI reconstructions have been used in numerous published studies now that range from modeling fire in the American West, to the impact of drought on palaeo-Indian societies, and to the determination of the primary causes of drought over North America through climate modeling experiments. Some examples of these applications will be described to illustrate the scientific value of these large-scale reconstructions of drought. Since the development and free public release of Version 1 of the North American Drought Atlas (see http:iridl.ldeo.columbia.edu/SOURCES/.LDEO/.TRL/.NADA2004/.pdsi-atlas.html), great improvements have been made in the critical tree-ring network used to reconstruct PDSI at each grid point. This network has now been enlarged to 1743 annual tree-ring chronologies, which greatly improves the density of tree-ring records in certain parts of the grid, especially in Canada and Mexico. In addition, the number of tree-ring records that extend back before AD 1400 has been substantially increased. These developments justify the creation of Version 2 of the North American Drought Atlas. In this talk I will describe this new version of the drought atlas and some of its properties that make it a significant improvement over the previous version. The new product provides enhanced resolution of the spatial and temporal variability of prolonged drought such as the late 16th century event that impacted regions of both Mexico and the United States. I will also argue for the North American Drought Atlas being used as a template for the development of large-scale drought reconstructions in other land areas of

  11. Prototypes for components of a control system for the ATLAS pixel detector at the HL-LHC

    International Nuclear Information System (INIS)

    Püllen, Lukas; Boek, Jennifer; Kersten, Susanne; Kind, Peter; Mättig, Peter; Zeitnitz, Christian

    2013-01-01

    In the years around 2020 an upgrade of the LHC to the HL-LHC is scheduled, which will increase the accelerator's instantaneous luminosity by a factor of 5 and the integrated luminosity by a factor of 10. In the context of this upgrade, the inner detector (including the pixel detector) of the ATLAS experiment will be replaced. This new pixel detector requires a specific control system which complies with strict requirements in terms of radiation hardness, material budget and space for the electronics in the ATLAS experiment. The University of Wuppertal is developing a concept for a DCS (Detector Control System) network consisting of two kinds of ASICs. The first ASIC is the DCS chip which is located on the pixel detector, very close to the interaction point. The second ASIC is the DCS Controller which is controlling 4×4 DCS chips from the outer regions of ATLAS via differential data lines. Both ASICs are manufactured in 130 nm deep sub-micron technology. We present results from reliability measurements under irradiation from new prototypes of components for the DCS network.

  12. Prototypes for components of a control system for the ATLAS pixel detector at the HL-LHC

    International Nuclear Information System (INIS)

    Boek, J; Kersten, S; Kind, P; Mättig, P; Püllen, L; Zeitnitz, C

    2013-01-01

    In the years around 2020 an upgrade of the LHC to the HL-LHC is scheduled, which will increase the accelerators luminosity by a factor of 10. In the context of this upgrade, the inner detector of the ATLAS experiment will be replaced entirely including the pixel detector. This new pixel detector requires a specific control system which complies with the strict requirements in terms of radiation hardness, material budget and space for the electronics in the ATLAS experiment. The University of Wuppertal is developing a concept for a DCS (Detector Control System) network consisting of two kinds of ASICs. The first ASIC is the DCS Chip which is located on the pixel detector, very close to the interaction point. The second ASIC is the DCS Controller which is controlling 4x4 DCS Chips from the outer regions of ATLAS via differential data lines. Both ASICs are manufactured in 130 nm deep sub micron technology. We present results from measurements from new prototypes of components for the DCS network.

  13. ATLAS Virtual Visits bringing the world into the ATLAS control room

    CERN Document Server

    AUTHOR|(CDS)2051192; The ATLAS collaboration; Yacoob, Sahal

    2016-01-01

    ATLAS Virtual Visits is a project initiated in 2011 for the Education & Outreach program of the ATLAS Experiment at CERN. Its goal is to promote public appreciation of the LHC physics program and particle physics, in general, through direct dialogue between ATLAS physicists and remote audiences. A Virtual Visit is an IP-based videoconference, coupled with a public webcast and video recording, between ATLAS physicists and remote locations around the world, that typically include high school or university classrooms, Masterclasses, science fairs, or other special events, usually hosted by collaboration members. Over the past two years, more than 10,000 people, from all of the world’s continents, have actively participated in ATLAS Virtual Visits, with many more enjoying the experience from the publicly available webcasts and recordings. We present an overview of our experience and discuss potential development for the future.

  14. Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm

    CERN Document Server

    Berghaus, Frank; The ATLAS collaboration

    2018-01-01

    The Simulation at Point1 (Sim@P1) project was built in 2013 to take advantage of the ATLAS Trigger and Data Acquisition High Level Trigger (HLT) farm. The HLT farm provides more than 2,000 compute nodes, which are critical to ATLAS during data taking. When ATLAS is not recording data, this large compute resource is used to generate and process simulation data for the experiment. The Sim@P1 system uses virtual machines, deployed by OpenStack, in order to isolate the resources from the ATLAS technical and control network. During the upcoming long shutdown in 2019 (LS2), the HLT farm including the Sim@P1 infrastructure will be upgraded. A previous paper on the project emphasized the need for “simple, reliable, and efficient tools” to quickly switch between data acquisition operation and offline processing.In this contribution we assess various options for updating and simplifying the provisional tools. Cloudscheduler is a tool for provisioning cloud resources for batch computing that has been managing cloud ...

  15. Supporting ATLAS

    CERN Multimedia

    maximilien brice

    2003-01-01

    Eighteen feet made of stainless steel will support the barrel ATLAS detector in the cavern at Point 1. In total, the ATLAS feet system will carry approximately 6000 tons, and will give the same inclination to the detector as the LHC accelerator.

  16. Integration of the Chinese HPC Grid in ATLAS Distributed Computing

    Science.gov (United States)

    Filipčič, A.; ATLAS Collaboration

    2017-10-01

    Fifteen Chinese High-Performance Computing sites, many of them on the TOP500 list of most powerful supercomputers, are integrated into a common infrastructure providing coherent access to a user through an interface based on a RESTful interface called SCEAPI. These resources have been integrated into the ATLAS Grid production system using a bridge between ATLAS and SCEAPI which translates the authorization and job submission protocols between the two environments. The ARC Computing Element (ARC-CE) forms the bridge using an extended batch system interface to allow job submission to SCEAPI. The ARC-CE was setup at the Institute for High Energy Physics, Beijing, in order to be as close as possible to the SCEAPI front-end interface at the Computing Network Information Center, also in Beijing. This paper describes the technical details of the integration between ARC-CE and SCEAPI and presents results so far with two supercomputer centers, Tianhe-IA and ERA. These two centers have been the pilots for ATLAS Monte Carlo Simulation in SCEAPI and have been providing CPU power since fall 2015.

  17. ATLAS Distributed Computing in LHC Run2

    CERN Document Server

    Campana, Simone; The ATLAS collaboration

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run2. An increased data rate and computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (ProdSys2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward the flexible computing model. The flexible computing utilization exploring the opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model, the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover a new data management strategy, based on defined lifetime for each dataset, has been defin...

  18. Report to users of Atlas

    International Nuclear Information System (INIS)

    Ahmad, I.; Glagola, B.

    1996-06-01

    This report contains the following topics: Status of the ATLAS Accelerator; Highlights of Recent Research at ATLAS; Program Advisory Committee; ATLAS User Group Executive Committee; FMA Information Available On The World Wide Web; Conference on Nuclear Structure at the Limits; and Workshop on Experiments with Gammasphere at ATLAS

  19. Two-stage atlas subset selection in multi-atlas based image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

    2015-06-15

    Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

  20. Two-stage atlas subset selection in multi-atlas based image segmentation.

    Science.gov (United States)

    Zhao, Tingting; Ruan, Dan

    2015-06-01

    Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas

  1. Two-stage atlas subset selection in multi-atlas based image segmentation

    International Nuclear Information System (INIS)

    Zhao, Tingting; Ruan, Dan

    2015-01-01

    Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

  2. The ATLAS Analysis Model

    CERN Multimedia

    Amir Farbin

    The ATLAS Analysis Model is a continually developing vision of how to reconcile physics analysis requirements with the ATLAS offline software and computing model constraints. In the past year this vision has influenced the evolution of the ATLAS Event Data Model, the Athena software framework, and physics analysis tools. These developments, along with the October Analysis Model Workshop and the planning for CSC analyses have led to a rapid refinement of the ATLAS Analysis Model in the past few months. This article introduces some of the relevant issues and presents the current vision of the future ATLAS Analysis Model. Event Data Model The ATLAS Event Data Model (EDM) consists of several levels of details, each targeted for a specific set of tasks. For example the Event Summary Data (ESD) stores calorimeter cells and tracking system hits thereby permitting many calibration and alignment tasks, but will be only accessible at particular computing sites with potentially large latency. In contrast, the Analysis...

  3. Danish heat atlas as a support tool for energy system models

    DEFF Research Database (Denmark)

    Petrovic, Stefan; Karlsson, Kenneth Bernard

    2014-01-01

    In the past four decades following the global oil crisis in 1973, Denmark has implemented remarkable changes in its energy sector, mainly due to the energy conservation measures on the demand side and the energy efficiency improvements on the supply side. Nowadays, the capital intensive infrastru......In the past four decades following the global oil crisis in 1973, Denmark has implemented remarkable changes in its energy sector, mainly due to the energy conservation measures on the demand side and the energy efficiency improvements on the supply side. Nowadays, the capital intensive...... infrastructure investments, such as the expansion of district heating networks and the introduction of significant heat saving measures require highly detailed decision-support tool. A Danish heat atlas provides highly detailed database with extensive information about more than 2.5 million buildings in Denmark...... society after 2050. The present paper shows how a Danish heat atlas can be used for providing inputs to energy system models, especially related to the analysis of heat saving measures within building stock and expansion of district heating networks. As a result, marginal cost curves are created...

  4. ATLAS Distributed Computing

    CERN Document Server

    Schovancova, J; The ATLAS collaboration

    2011-01-01

    The poster details the different aspects of the ATLAS Distributed Computing experience after the first year of LHC data taking. We describe the performance of the ATLAS distributed computing system and the lessons learned during the 2010 run, pointing out parts of the system which were in a good shape, and also spotting areas which required improvements. Improvements ranged from hardware upgrade on the ATLAS Tier-0 computing pools to improve data distribution rates, tuning of FTS channels between CERN and Tier-1s, and studying data access patterns for Grid analysis to improve the global processing rate. We show recent software development driven by operational needs with emphasis on data management and job execution in the ATLAS production system.

  5. ATLAS Review Office

    CERN Multimedia

    Szeless, B

    The ATLAS internal reviews, be it the mandatory Production Readiness Reviews, the now newly installed Production Advancement Reviews, or the more and more requested different Design Reviews, have become a part of our ATLAS culture over the past years. The Activity Systems Status Overviews are, for the time being, a one in time event and should be held for each system as soon as possible to have some meaning. There seems to a consensus that the reviews have become a useful project tool for the ATLAS management but even more so for the sub-systems themselves making achievements as well as possible shortcomings visible. One other recognized byproduct is the increasing cross talk between the systems, a very important ingredient to make profit all the systems from the large collective knowledge we dispose of in ATLAS. In the last two months, the first two PARs were organized for the MDT End Caps and the TRT Barrel Modules, both part of the US contribution to the ATLAS Project. Furthermore several different design...

  6. Berliner Philarmoniker ATLAS visit

    CERN Multimedia

    ATLAS Collaboration

    2017-01-01

    The Berliner Philarmoniker in on tour through Europe. They stopped on June 27th in Geneva, for a concert at the Victoria Hall. An ATLAS visit was organised the morning after, lead by the ATLAS spokesperson Karl Jakobs (welcome and overview talk) and two ATLAS guides (AVC visit and 3D movie).

  7. Software Validation in ATLAS

    International Nuclear Information System (INIS)

    Hodgkinson, Mark; Seuster, Rolf; Simmons, Brinick; Sherwood, Peter; Rousseau, David

    2012-01-01

    The ATLAS collaboration operates an extensive set of protocols to validate the quality of the offline software in a timely manner. This is essential in order to process the large amounts of data being collected by the ATLAS detector in 2011 without complications on the offline software side. We will discuss a number of different strategies used to validate the ATLAS offline software; running the ATLAS framework software, Athena, in a variety of configurations daily on each nightly build via the ATLAS Nightly System (ATN) and Run Time Tester (RTT) systems; the monitoring of these tests and checking the compilation of the software via distributed teams of rotating shifters; monitoring of and follow up on bug reports by the shifter teams and periodic software cleaning weeks to improve the quality of the offline software further.

  8. ATLAS Open Data project

    CERN Document Server

    The ATLAS collaboration

    2018-01-01

    The current ATLAS model of Open Access to recorded and simulated data offers the opportunity to access datasets with a focus on education, training and outreach. This mandate supports the creation of platforms, projects, software, and educational products used all over the planet. We describe the overall status of ATLAS Open Data (http://opendata.atlas.cern) activities, from core ATLAS activities and releases to individual and group efforts, as well as educational programs, and final web or software-based (and hard-copy) products that have been produced or are under development. The relatively large number and heterogeneous use cases currently documented is driving an upcoming release of more data and resources for the ATLAS Community and anyone interested to explore the world of experimental particle physics and the computer sciences through data analysis.

  9. AGIS: The ATLAS Grid Information System

    CERN Document Server

    Anisenkov, A; The ATLAS collaboration; Klimentov, A; Senchenko, A

    2012-01-01

    The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

  10. Cartea de Colorat a Experimentului ATLAS - ATLAS Experiment Colouring Book in Romanian

    CERN Multimedia

    Anthony, Katarina

    2018-01-01

    Language: Romanian - The ATLAS Experiment Colouring Book is a free-to-download educational book, ideal for kids aged 5-9. It aims to introduce children to the field of High-Energy Physics, as well as the work being carried out by the ATLAS Collaboration. Limba: Română - Cartea de Colorat a Experimentului ATLAS este o carte educativă gratuită, ideală pentru copiii cu vârsta cuprinsă între 5-9 ani. Scopul său este de a introduce copii în domeniul fizicii de înaltă energie, precum și activitatea desfășurată de colaborarea ATLAS.

  11. An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases.

    Science.gov (United States)

    Forbes, Jessica L; Kim, Regina E Y; Paulsen, Jane S; Johnson, Hans J

    2016-01-01

    The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%.

  12. Achievements of the ATLAS Distributed Analysis during the first run period

    CERN Document Server

    Farida, Fassi; The ATLAS collaboration

    2013-01-01

    Summary : In the LHC operations era analyzing the large data by the distributed physicists becomes a challenging task. The Computing Model of the ATLAS experiment at the LHC at CERN was designed around the concepts of grid computing. Large data volumes from the detectors and simulations require a large number of CPUs and storage space for data processing. To cope with these challenges a global network known as the Worlwide LHC Computing Grid (WLCG) was built. This is the most sophisticated data taking and analysis system ever built. Since the start of data-taking, the ATLAS Distributed Analysis (ADA) service has been running stably with the huge amount of data. The reliability of the ADA service is high but steadily improving; grid sites are continually validated against a set of standard tests, and a dedicated team of expert shifters provides user support and communicates user problems to the sites. The ATLAS Grid Computing Model is reviewed in this talk. Emphasis is given to ADA system. Description : The ce...

  13. AGIS: The ATLAS Grid Information System

    CERN Document Server

    Anisenkov, Alexey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

    2012-01-01

    ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

  14. Computational and mathematical methods in brain atlasing.

    Science.gov (United States)

    Nowinski, Wieslaw L

    2017-12-01

    Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

  15. Wind Atlas for Egypt

    DEFF Research Database (Denmark)

    The results of a comprehensive, 8-year wind resource assessment programme in Egypt are presented. The objective has been to provide reliable and accurate wind atlas data sets for evaluating the potential wind power output from large electricityproducing wind turbine installations. The regional wind...... climates of Egypt have been determined by two independent methods: a traditional wind atlas based on observations from more than 30 stations all over Egypt, and a numerical wind atlas based on long-term reanalysis data and a mesoscale model (KAMM). The mean absolute error comparing the two methods is about...... 10% for two large-scale KAMM domains covering all of Egypt, and typically about 5% for several smaller-scale regional domains. The numerical wind atlas covers all of Egypt, whereas the meteorological stations are concentrated in six regions. The Wind Atlas for Egypt represents a significant step...

  16. Wind Atlas for Egypt

    DEFF Research Database (Denmark)

    Mortensen, Niels Gylling; Said Said, Usama; Badger, Jake

    2006-01-01

    The results of a comprehensive, 8-year wind resource assessment programme in Egypt are presented. The objective has been to provide reliable and accurate wind atlas data sets for evaluating the potential wind power output from large electricityproducing wind turbine installations. The regional wind...... climates of Egypt have been determined by two independent methods: a traditional wind atlas based on observations from more than 30 stations all over Egypt, and a numerical wind atlas based on long-term reanalysis data and a mesoscale model (KAMM). The mean absolute error comparing the two methods is about...... 10% for two large-scale KAMM domains covering all of Egypt, and typically about 5% for several smaller-scale regional domains. The numerical wind atlas covers all of Egypt, whereas the meteorological stations are concentrated in six regions. The Wind Atlas for Egypt represents a significant step...

  17. Recent ATLAS Articles on WLAP

    CERN Multimedia

    Goldfarb, S.

    As reported in the September 2004 ATLAS eNews, the Web Lecture Archive Project is a system for the archiving and publishing of multimedia presentations, using the Web as medium. We list here newly available WLAP items relating to ATLAS: June ATLAS Plenary Meeting Tutorial on Physics EDM and Tools (June) Freiburg Overview Week Ketevi Assamagan's Tutorial on Analysis Tools Click here to browse WLAP for all ATLAS lectures.

  18. Estimate of the neutron fields in ATLAS based on ATLAS-MPX detectors data

    International Nuclear Information System (INIS)

    Bouchami, J; Dallaire, F; Gutierrez, A; Idarraga, J; Leroy, C; Picard, S; Scallon, O; Kral, V; PospIsil, S; Solc, J; Suk, M; Turecek, D; Vykydal, Z; Zemlieka, J

    2011-01-01

    The ATLAS-MPX detectors are based on Medipix2 silicon devices designed by CERN for the detection of different types of radiation. These detectors are covered with converting layers of 6 LiF and polyethylene (PE) to increase their sensitivity to thermal and fast neutrons, respectively. These devices allow the measurement of the composition and spectroscopic characteristics of the radiation field in ATLAS, particularly of neutrons. These detectors can operate in low or high preset energy threshold mode. The signature of particles interacting in a ATLAS-MPX detector at low threshold are clusters of adjacent pixels with different size and form depending on their type, energy and incidence angle. The classification of particles into different categories can be done using the geometrical parameters of these clusters. The Medipix analysis framework (MAFalda) - based on the ROOT application - allows the recognition of particle tracks left in ATLAS-MPX devices located at various positions in the ATLAS detector and cavern. The pattern recognition obtained from the application of MAFalda was configured to distinguish the response of neutrons from other radiation. The neutron response at low threshold is characterized by clusters of adjoining pixels (heavy tracks and heavy blobs) left by protons and heavy ions resulting from neutron interactions in the converting layers of the ATLAS-MPX devices. The neutron detection efficiency of ATLAS-MPX devices has been determined by the exposure of two detectors of reference to radionuclide sources of neutrons ( 252 Cf and 241 AmBe). With these results, an estimate of the neutrons fields produced at the devices locations during ATLAS operation was done.

  19. Analysis Facility infrastructure (TIER3) for ATLAS High Energy physics experiment

    International Nuclear Information System (INIS)

    Gonzalez de la Hoz, S.; March, L.; Ros, E.; Sanchez, J.; Amoros, G.; Fassi, F.; Fernandez, A.; Kaci, M.; Lamas, A.; Salt, J.

    2007-01-01

    ATLAS project has been asked to define the scope and role of Tier-3 resources (facilities or centres) within the existing ATLAS computing model, activities and facilities. This document attempts to address these questions by describing Tier-3 resources generally, and their relationship to the ATLAS Software and Computing Project. Originally the tiered computing model came out of MONARC (see http://monarc.web.cern.ch/MONARC/) work and was predicated upon the network being a scarce resource. In this model the tiered hierarchy ranged from the Tier-0 (CERN) down to the desktop or workstation (Tier 3). The focus on defining the roles of each tiered component has evolved with the initial emphasis on the Tier-0 (CERN) and Tier-1 (National centres) definition and roles. The various LHC projects, including ATLAS, then evolved the tiered hierarchy to include Tier-2s (Regional centers) as part of their projects. Tier-3s, on the other hand, have (implicitly and sometime explicitly) been defined as whatever an institution could construct to support their Physics goals using institutional and otherwise leveraged resources and therefore have not been considered to be part of the official ATLAS Research Program computing resources nor under their control, meaning there is no formal MOU process to designate sites as Tier-3s and no formal control of the program over the Tier-3 resources. Tier-3s are the responsibility of individual institutions to define, fund, deploy and support. However, having noted this, we must also recognize that Tier-3s must exist and will have implications for how our computing model should support ATLAS physicists. Tier-3 users will want to access data and simulations and will want to enable their Tier-3 resources to support their analysis and simulation work. Tiers 3s are an important resource for physicists to analyze LHC (Large Hadron Collider) data. This document will define how Tier-3s should best interact with the ATLAS computing model, detail the

  20. Experience running a distributed Tier-2 in Spain for the ATLAS experiment

    International Nuclear Information System (INIS)

    March, L; Hoz, S Gonzales de la; Kaci, M; Fassi, F; Fernandez, A; Lamas, A; Salt, J; Sanchez, J; Peso, J del; Fernandez, P; Munoz, L; Pardo, J; Espinal, X; Garitaonandia, H; Mir, M L; Nadal, J; Pacheco, A; Shuskov, S

    2008-01-01

    The main role of the Tier-2s is to provide computing resources for production of physics simulated events and distributed data analysis. The Spanish ATLAS Tier-2 is geographically distributed among three HEP institutes: IFAE (Barcelona), IFIC (Valencia) and UAM (Madrid). Currently it has a computing power of 430 kSI2K CPU, a disk storage capacity of 87 TB and a network bandwidth, connecting the three sites and the nearest Tier-1 (PIC), of 1 Gb/s. These resources will be increased according to the ATLAS Computing Model with time in parallel to those of all ATLAS Tier-2s. Since 2002, it has been participating into the different Data Challenge exercises. Currently, it is achieving around 1.5% of the whole ATLAS collaboration production in the framework of the Computing System Commissioning exercise. A distributed data management is also arising as an important issue in the daily activities of the Tier-2. The distribution in three sites has shown to be useful due to an increasing service redundancy, a faster solution of problems, the share of computing expertise and know-how. Experience gained running the distributed Tier-2 in order to be ready at the LHC start-up will be presented

  1. Frameworks to monitor and predict resource usage in the ATLAS High Level Trigger

    CERN Document Server

    Martin, Tim; The ATLAS collaboration

    2016-01-01

    The ATLAS High Level Trigger Farm consists of around 30,000 CPU cores which filter events at up to 100 kHz input rate. A costing framework is built into the high level trigger, this enables detailed monitoring of the system and allows for data-driven predictions to be made utilising specialist datasets. This talk will present an overview of how ATLAS collects in-situ monitoring data on both CPU usage and dataflow over the data-acquisition network during the trigger execution, and how these data are processed to yield both low level monitoring of individual selection-algorithms and high level data on the overall performance of the farm. For development and prediction purposes, ATLAS uses a special `Enhanced Bias' event selection. This mechanism will be explained along with how is used to profile expected resource usage and output event-rate of new physics selections, before they are executed on the actual high level trigger farm.

  2. Effets de rayonnement sur les detecteurs au silicium a pixels du detecteur ATLAS

    CERN Document Server

    Lebel, Celine

    2007-01-01

    Two detection systems are using pixel silicon detectors in the ATLAS detector: the Pixel, which is the subdetector closest to the interaction point, and the MPX network. The activation of the materials present in the Pixel produced by radiation has been measured in two experiments which we performed at CERF (CERN) and NPI-ASCR (Czech Republic). These experimental studies of activation are com- pared with GEANT4 simulations. The results of these comparisons show that the simulation can predict the activities with a precision of an order of magnitude. They also show that GEANT4 fails to produce certain radioisotopes seen in the experimental activation studies. The contribution to background and the resid- ual doses due to the desintegration of the radioisotopes produced by fast neutrons (category in which falls the expected average neutron energy of 1 MeV in ATLAS) are extrapolated to ATLAS conditions. It is found that this background in the AT- LAS Pixel subdetector will be negligible and that the doses are we...

  3. PanDA: Exascale Federation of Resources for the ATLAS Experiment at the LHC

    Directory of Open Access Journals (Sweden)

    Megino Fernando Barreiro

    2016-01-01

    The PanDA (Production and Distributed Analysis system was developed in 2005 for the ATLAS experiment on top of this heterogeneous infrastructure to seamlessly integrate the computational resources and give the users the feeling of a unique system. Since its origins, PanDA has evolved together with upcoming computing paradigms in and outside HEP, such as changes in the networking model, Cloud Computing and HPC. It is currently running steadily up to 200 thousand simultaneous cores (limited by the available resources for ATLAS, up to two million aggregated jobs per day and processes over an exabyte of data per year. The success of PanDA in ATLAS is triggering the widespread adoption and testing by other experiments. In this contribution we will give an overview of the PanDA components and focus on the new features and upcoming challenges that are relevant to the next decade of distributed computing workload management using PanDA.

  4. Implementation of the ATLAS trigger within the ATLAS Multi­Threaded Software Framework AthenaMT

    CERN Document Server

    Wynne, Benjamin; The ATLAS collaboration

    2016-01-01

    We present an implementation of the ATLAS High Level Trigger that provides parallel execution of trigger algorithms within the ATLAS multi­threaded software framework, AthenaMT. This development will enable the ATLAS High Level Trigger to meet future challenges due to the evolution of computing hardware and upgrades of the Large Hadron Collider, LHC, and ATLAS Detector. During the LHC data­taking period starting in 2021, luminosity will reach up to three times the original design value. Luminosity will increase further, to up to 7.5 times the design value, in 2026 following LHC and ATLAS upgrades. This includes an upgrade of the ATLAS trigger architecture that will result in an increase in the High Level Trigger input rate by a factor of 4 to 10 compared to the current maximum rate of 100 kHz. The current ATLAS multiprocess framework, AthenaMP, manages a number of processes that process events independently, executing algorithms sequentially in each process. AthenaMT will provide a fully multi­threaded env...

  5. Report to users of ATLAS

    International Nuclear Information System (INIS)

    Ahmad, I.; Glagola, B.

    1997-03-01

    This report covers the following topics: (1) status of the ATLAS accelerator; (2) progress in R and D towards a proposal for a National ISOL Facility; (3) highlights of recent research at ATLAS; (4) the move of gammasphere from LBNL to ANL; (5) Accelerator Target Development laboratory; (6) Program Advisory Committee; (7) ATLAS User Group Executive Committee; and (8) ATLAS user handbook available in the World Wide Web. A brief summary is given for each topic

  6. Estimate of the neutron fields in ATLAS based on ATLAS-MPX detectors data

    Energy Technology Data Exchange (ETDEWEB)

    Bouchami, J; Dallaire, F; Gutierrez, A; Idarraga, J; Leroy, C; Picard, S; Scallon, O [Universite de Montreal, Montreal, Quebec H3C 3J7 (Canada); Kral, V; PospIsil, S; Solc, J; Suk, M; Turecek, D; Vykydal, Z; Zemlieka, J, E-mail: scallon@lps.umontreal.ca [Institute of Experimental and Applied Physics of the CTU in Prague, Horska 3a/22, CZ-12800 Praha2 - Albertov (Czech Republic)

    2011-01-15

    The ATLAS-MPX detectors are based on Medipix2 silicon devices designed by CERN for the detection of different types of radiation. These detectors are covered with converting layers of {sup 6}LiF and polyethylene (PE) to increase their sensitivity to thermal and fast neutrons, respectively. These devices allow the measurement of the composition and spectroscopic characteristics of the radiation field in ATLAS, particularly of neutrons. These detectors can operate in low or high preset energy threshold mode. The signature of particles interacting in a ATLAS-MPX detector at low threshold are clusters of adjacent pixels with different size and form depending on their type, energy and incidence angle. The classification of particles into different categories can be done using the geometrical parameters of these clusters. The Medipix analysis framework (MAFalda) - based on the ROOT application - allows the recognition of particle tracks left in ATLAS-MPX devices located at various positions in the ATLAS detector and cavern. The pattern recognition obtained from the application of MAFalda was configured to distinguish the response of neutrons from other radiation. The neutron response at low threshold is characterized by clusters of adjoining pixels (heavy tracks and heavy blobs) left by protons and heavy ions resulting from neutron interactions in the converting layers of the ATLAS-MPX devices. The neutron detection efficiency of ATLAS-MPX devices has been determined by the exposure of two detectors of reference to radionuclide sources of neutrons ({sup 252}Cf and {sup 241}AmBe). With these results, an estimate of the neutrons fields produced at the devices locations during ATLAS operation was done.

  7. Estimate of the neutron fields in ATLAS based on ATLAS-MPX detectors data

    Science.gov (United States)

    Bouchami, J.; Dallaire, F.; Gutiérrez, A.; Idarraga, J.; Král, V.; Leroy, C.; Picard, S.; Pospíšil, S.; Scallon, O.; Solc, J.; Suk, M.; Turecek, D.; Vykydal, Z.; Žemlièka, J.

    2011-01-01

    The ATLAS-MPX detectors are based on Medipix2 silicon devices designed by CERN for the detection of different types of radiation. These detectors are covered with converting layers of 6LiF and polyethylene (PE) to increase their sensitivity to thermal and fast neutrons, respectively. These devices allow the measurement of the composition and spectroscopic characteristics of the radiation field in ATLAS, particularly of neutrons. These detectors can operate in low or high preset energy threshold mode. The signature of particles interacting in a ATLAS-MPX detector at low threshold are clusters of adjacent pixels with different size and form depending on their type, energy and incidence angle. The classification of particles into different categories can be done using the geometrical parameters of these clusters. The Medipix analysis framework (MAFalda) — based on the ROOT application — allows the recognition of particle tracks left in ATLAS-MPX devices located at various positions in the ATLAS detector and cavern. The pattern recognition obtained from the application of MAFalda was configured to distinguish the response of neutrons from other radiation. The neutron response at low threshold is characterized by clusters of adjoining pixels (heavy tracks and heavy blobs) left by protons and heavy ions resulting from neutron interactions in the converting layers of the ATLAS-MPX devices. The neutron detection efficiency of ATLAS-MPX devices has been determined by the exposure of two detectors of reference to radionuclide sources of neutrons (252Cf and 241AmBe). With these results, an estimate of the neutrons fields produced at the devices locations during ATLAS operation was done.

  8. ATLAS Colouring Book

    CERN Multimedia

    Anthony, Katarina

    2016-01-01

    The ATLAS Experiment Colouring Book is a free-to-download educational book, ideal for kids aged 5-9. It aims to introduce children to the field of High-Energy Physics, as well as the work being carried out by the ATLAS Collaboration.

  9. SU-E-J-128: Two-Stage Atlas Selection in Multi-Atlas-Based Image Segmentation

    International Nuclear Information System (INIS)

    Zhao, T; Ruan, D

    2015-01-01

    Purpose: In the new era of big data, multi-atlas-based image segmentation is challenged by heterogeneous atlas quality and high computation burden from extensive atlas collection, demanding efficient identification of the most relevant atlases. This study aims to develop a two-stage atlas selection scheme to achieve computational economy with performance guarantee. Methods: We develop a low-cost fusion set selection scheme by introducing a preliminary selection to trim full atlas collection into an augmented subset, alleviating the need for extensive full-fledged registrations. More specifically, fusion set selection is performed in two successive steps: preliminary selection and refinement. An augmented subset is first roughly selected from the whole atlas collection with a simple registration scheme and the corresponding preliminary relevance metric; the augmented subset is further refined into the desired fusion set size, using full-fledged registration and the associated relevance metric. The main novelty of this work is the introduction of an inference model to relate the preliminary and refined relevance metrics, based on which the augmented subset size is rigorously derived to ensure the desired atlases survive the preliminary selection with high probability. Results: The performance and complexity of the proposed two-stage atlas selection method were assessed using a collection of 30 prostate MR images. It achieved comparable segmentation accuracy as the conventional one-stage method with full-fledged registration, but significantly reduced computation time to 1/3 (from 30.82 to 11.04 min per segmentation). Compared with alternative one-stage cost-saving approach, the proposed scheme yielded superior performance with mean and medium DSC of (0.83, 0.85) compared to (0.74, 0.78). Conclusion: This work has developed a model-guided two-stage atlas selection scheme to achieve significant cost reduction while guaranteeing high segmentation accuracy. The benefit

  10. ATLAS Cloud R&D

    CERN Document Server

    Panitkin, S; The ATLAS collaboration; Caballero Bejar, J; Benjamin, D; DiGirolamo, A; Gable, I; Hendrix, V; Hover, J; Kucharczuk, K; Medrano LLamas, R; Love, P; Ohman, H; Paterson, M; Sobie, R; Taylor, R; Walker, R; Zaytsev, A

    2014-01-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained...

  11. ATLAS MPGD production status

    CERN Document Server

    Schioppa, Marco; The ATLAS collaboration

    2018-01-01

    Micromegas (MICRO MEsh GAseous Structure) chambers are Micro-Pattern Gaseous Detectors designed to provide a high spatial resolution and reasonable good time resolution in highly irradiated environments. In 2007 an ambitious long-term R\\&D activity was started in the context of the ATLAS experiment, at CERN: the Muon ATLAS Micromegas Activity (MAMMA). After years of tests on prototypes and technology breakthroughs, Micromegas chambers were chosen as tracking detectors for an upgrade of the ATLAS Muon Spectrometer. These novel detectors will be installed in 2020 at the end of the second long shutdown of the Large Hadron Collider, and will serve mainly as precision detectors in the innermost part of the forward ATLAS Muon Spectrometer. Four different types of Micromegas modules, eight layers each, up to $3 m^2$ area (of unprecedented size), will cover a surface of $150 m^2$ for a total active area of about $1200 m^2$. With this upgrade the ATLAS muon system will maintain the full acceptance of its excellent...

  12. ATLAS' major cooling project

    CERN Multimedia

    2005-01-01

    In 2005, a considerable effort has been put into commissioning the various units of ATLAS' complex cryogenic system. This is in preparation for the imminent cooling of some of the largest components of the detector in their final underground configuration. The liquid helium and nitrogen ATLAS refrigerators in USA 15. Cryogenics plays a vital role in operating massive detectors such as ATLAS. In many ways the liquefied argon, nitrogen and helium are the life-blood of the detector. ATLAS could not function without cryogens that will be constantly pumped via proximity systems to the superconducting magnets and subdetectors. In recent weeks compressors at the surface and underground refrigerators, dewars, pumps, linkages and all manner of other components related to the cryogenic system have been tested and commissioned. Fifty metres underground The helium and nitrogen refrigerators, installed inside the service cavern, are an important part of the ATLAS cryogenic system. Two independent helium refrigerators ...

  13. ATLAS: Exceeding all expectations

    CERN Multimedia

    CERN Bulletin

    2010-01-01

    “One year ago it would have been impossible for us to guess that the machine and the experiments could achieve so much so quickly”, says Fabiola Gianotti, ATLAS spokesperson. The whole chain – from collision to data analysis – has worked remarkably well in ATLAS.   The first LHC proton run undoubtedly exceeded expectations for the ATLAS experiment. “ATLAS has worked very well since the beginning. Its overall data-taking efficiency is greater than 90%”, says Fabiola Gianotti. “The quality and maturity of the reconstruction and simulation software turned out to be better than we expected for this initial stage of the experiment. The Grid is a great success, and right from the beginning it has allowed members of the collaboration all over the world to participate in the data analysis in an effective and timely manner, and to deliver physics results very quickly”. In just a few months of data taking, ATLAS has observed t...

  14. Future ATLAS Higgs Studies

    CERN Document Server

    Smart, Ben; The ATLAS collaboration

    2017-01-01

    The High-Luminosity LHC will prove a challenging environment to work in, with for example $=200$ expected. It will however also provide great opportunities for advancing studies of the Higgs boson. The ATLAS detector will be upgraded, and Higgs prospects analyses have been performed to assess the reach of ATLAS Higgs studies in the HL-LHC era. These analyses are presented, as are Run-2 ATLAS di-Higgs analyses for comparison.

  15. Baby brain atlases.

    Science.gov (United States)

    Oishi, Kenichi; Chang, Linda; Huang, Hao

    2018-04-03

    The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide neuroscientists and clinicians in their investigation of this frontier, maps of the baby brain, which contain a priori knowledge about neurodevelopment and anatomy, are essential. "Brain atlas" in this review refers to a 3D-brain image with a set of reference labels, such as a parcellation map, as the anatomical reference that guides the mapping of the brain. Recent advancements in scanners, sequences, and motion control methodologies enable the creation of various types of high-resolution baby brain atlases. What is becoming clear is that one atlas is not sufficient to characterize the existing knowledge about the anatomical variations, disease-related anatomical alterations, and the variations in time-dependent changes. In this review, the types and roles of the human baby brain MRI atlases that are currently available are described and discussed, and future directions in the field of developmental neuroscience and its clinical applications are proposed. The potential use of disease-based atlases to characterize clinically relevant information, such as clinical labels, in addition to conventional anatomical labels, is also discussed. Copyright © 2018. Published by Elsevier Inc.

  16. Glance Information System for ATLAS Management

    International Nuclear Information System (INIS)

    Grael, F F; Maidantchik, C; Évora, L H R A; Karam, K; Moraes, L O F; Cirilli, M; Nessi, M; Pommès, K

    2011-01-01

    ATLAS Experiment is an international collaboration where more than 37 countries, 172 institutes and laboratories, 2900 physicists, engineers, and computer scientists plus 700 students participate. The management of this teamwork involves several aspects such as institute contribution, employment records, members' appointment, authors' list, preparation and publication of papers and speakers nomination. Previously, most of the information was accessible by a limited group and developers had to face problems such as different terminology, diverse data modeling, heterogeneous databases and unlike users needs. Moreover, the systems were not designed to handle new requirements. The maintenance has to be an easy task due to the long lifetime experiment and professionals turnover. The Glance system, a generic mechanism for accessing any database, acts as an intermediate layer isolating the user from the particularities of each database. It retrieves, inserts and updates the database independently of its technology and modeling. Relying on Glance, a group of systems were built to support the ATLAS management and operation aspects: ATLAS Membership, ATLAS Appointments, ATLAS Speakers, ATLAS Analysis Follow-Up, ATLAS Conference Notes, ATLAS Thesis, ATLAS Traceability and DSS Alarms Viewer. This paper presents the overview of the Glance information framework and describes the privilege mechanism developed to grant different level of access for each member and system.

  17. Glance Information System for ATLAS Management

    Science.gov (United States)

    Grael, F. F.; Maidantchik, C.; Évora, L. H. R. A.; Karam, K.; Moraes, L. O. F.; Cirilli, M.; Nessi, M.; Pommès, K.; ATLAS Collaboration

    2011-12-01

    ATLAS Experiment is an international collaboration where more than 37 countries, 172 institutes and laboratories, 2900 physicists, engineers, and computer scientists plus 700 students participate. The management of this teamwork involves several aspects such as institute contribution, employment records, members' appointment, authors' list, preparation and publication of papers and speakers nomination. Previously, most of the information was accessible by a limited group and developers had to face problems such as different terminology, diverse data modeling, heterogeneous databases and unlike users needs. Moreover, the systems were not designed to handle new requirements. The maintenance has to be an easy task due to the long lifetime experiment and professionals turnover. The Glance system, a generic mechanism for accessing any database, acts as an intermediate layer isolating the user from the particularities of each database. It retrieves, inserts and updates the database independently of its technology and modeling. Relying on Glance, a group of systems were built to support the ATLAS management and operation aspects: ATLAS Membership, ATLAS Appointments, ATLAS Speakers, ATLAS Analysis Follow-Up, ATLAS Conference Notes, ATLAS Thesis, ATLAS Traceability and DSS Alarms Viewer. This paper presents the overview of the Glance information framework and describes the privilege mechanism developed to grant different level of access for each member and system.

  18. ATLAS Cloud R&D

    Science.gov (United States)

    Panitkin, Sergey; Barreiro Megino, Fernando; Caballero Bejar, Jose; Benjamin, Doug; Di Girolamo, Alessandro; Gable, Ian; Hendrix, Val; Hover, John; Kucharczyk, Katarzyna; Medrano Llamas, Ramon; Love, Peter; Ohman, Henrik; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Walker, Rodney; Zaytsev, Alexander; Atlas Collaboration

    2014-06-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

  19. The Irish Wind Atlas

    Energy Technology Data Exchange (ETDEWEB)

    Watson, R [Univ. College Dublin, Dept. of Electronic and Electrical Engineering, Dublin (Ireland); Landberg, L [Risoe National Lab., Meteorology and Wind Energy Dept., Roskilde (Denmark)

    1999-03-01

    The development work on the Irish Wind Atlas is nearing completion. The Irish Wind Atlas is an updated improved version of the Irish section of the European Wind Atlas. A map of the irish wind resource based on a WA{sup s}P analysis of the measured data and station description of 27 measuring stations is presented. The results of previously presented WA{sup s}P/KAMM runs show good agreement with these results. (au)

  20. O Livro de Colorir da Experiência ATLAS - ATLAS Experiment Colouring Book in Portuguese

    CERN Multimedia

    Anthony, Katarina

    2017-01-01

    Language: Portuguese - The ATLAS Experiment Colouring Book is a free-to-download educational book, ideal for kids aged 5-9. It aims to introduce children to the field of High-Energy Physics, as well as the work being carried out by the ATLAS Collaboration. Língua: Português - O Livro de Colorir da Experiência ATLAS é um livro educacional gratuito para descarregar, ideal para crianças dos 5 aos 9 anos de idade. Este livro procura introduzir as crianças ao estudo da Física de Alta-Energia, bem como ao trabalho desenvolvido pela Colaboração ATLAS.

  1. Maľovanka Experiment ATLAS - ATLAS Experiment Colouring Book in Slovak

    CERN Multimedia

    Anthony, Katarina

    2017-01-01

    Language: Slovak - The ATLAS Experiment Colouring Book is a free-to-download educational book, ideal for kids aged 5-9. It aims to introduce children to the field of High-Energy Physics, as well as the work being carried out by the ATLAS Collaboration.

  2. ATLAS Deneyi Boyama Kitabı - ATLAS Experiment Colouring Book in Turkish

    CERN Multimedia

    Anthony, Katarina

    2018-01-01

    Language: Turkish - The ATLAS Experiment Colouring Book is a free-to-download educational book, ideal for kids aged 5-9. It aims to introduce children to the field of High-Energy Physics, as well as the work being carried out by the ATLAS Collaboration.

  3. AGIS: The ATLAS Grid Information System

    Science.gov (United States)

    Anisenkov, A.; Di Girolamo, A.; Klimentov, A.; Oleynik, D.; Petrosyan, A.; Atlas Collaboration

    2014-06-01

    ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produced petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we describe the ATLAS Grid Information System (AGIS), designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

  4. A major upgrade of the sediment echosounder ATLAS PARASOUND and the digital acquisition software ParaDigMA for high-resolution sea floor studies

    Science.gov (United States)

    Gerriets, A.; von Lom-Keil, H.; Spiess, V.; Zwanzig, C.; Bruns, R.

    2003-04-01

    The combination of the ATLAS PARASOUND sediment echosounder, designed by ATLAS Hydrographic, and the digital recording software package ParaDigMA (commercially available as ATLAS PARASTORE-3) for online digitisation, preprocessing and visualisation of recorded seismograms has proven to be a reliable system for high-resolution acoustic sea floor studies. During 10 years of successful operation aboard several research vessels, including R/V Meteor, R/V Sonne and R/V Polarstern, the system has been only slightly modified. Based on this experience, today's PARASOUND/ParaDigMA system has accomplished the step from DOS towards Windows platform and network capability. In cooperation of ATLAS Hydrographic and the Department of Earth Sciences, University of Bremen a major upgrade of the PARASOUND/ParaDigMA system has been developed that adds significant functionality for surveys of sediment structures and sea floor morphology. The innovations primarily concern the control section of the ATLAS PARASOUND echosounder and the ParaDigMA user front end. The previous analogue PARASOUND control terminal has been replaced by a small real time control PC responsible for the control of the echosounder as well as for the continuous digitisation of the data. The control PC communicates via standard network protocols metadata and data with client applications that can display and store the acquired data on different computers on the network. The new network capabilities of the system overcome former limitations and admit a high flexibility with respect to numbers and locations of operator and recording/display PCs. The system now offers a simultaneous parallel registration of the 2.5-5.5kHz parametric signal and the 18kHz NBS signal. This feature in combination with the recording of complete soundings including the entire water column provides the basis for evolving scientific research topics e. g. gas venting. The ParaDigMA recording software now operates on Windows platforms which

  5. The Cerefy Neuroradiology Atlas: a Talairach-Tournoux atlas-based tool for analysis of neuroimages available over the internet.

    Science.gov (United States)

    Nowinski, Wieslaw L; Belov, Dmitry

    2003-09-01

    The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.

  6. An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man

    KAUST Repository

    Ravasi, Timothy; Suzuki, Harukazu; Cannistraci, Carlo; Katayama, Shintaro; Bajic, Vladimir B.; Tan, Kai; Akalin, Altuna; Schmeier, Sebastian; Kanamori-Katayama, Mutsumi; Bertin, Nicolas; Carninci, Piero; Daub, Carsten O.; Forrest, Alistair R.R.; Gough, Julian; Grimmond, Sean; Han, Jung-Hoon; Hashimoto, Takehiro; Hide, Winston; Hofmann, Oliver; Kamburov, Atanas; Kaur, Mandeep; Kawaji, Hideya; Kubosaki, Atsutaka; Lassmann, Timo; van Nimwegen, Erik; MacPherson, Cameron Ross; Ogawa, Chihiro; Radovanovic, Aleksandar; Schwartz, Ariel; Teasdale, Rohan D.; Tegné r, Jesper; Lenhard, Boris; Teichmann, Sarah A.; Arakawa, Takahiro; Ninomiya, Noriko; Murakami, Kayoko; Tagami, Michihira; Fukuda, Shiro; Imamura, Kengo; Kai, Chikatoshi; Ishihara, Ryoko; Kitazume, Yayoi; Kawai, Jun; Hume, David A.; Ideker, Trey; Hayashizaki, Yoshihide

    2010-01-01

    Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

  7. An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man

    KAUST Repository

    Ravasi, Timothy

    2010-03-01

    Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

  8. Development of fluorocarbon evaporative cooling recirculators and controls for the ATLAS inner silicon tracker

    CERN Document Server

    Bayer, C; Bonneau, P; Bosteels, Michel; Burckhart, H J; Cragg, D; English, R; Hallewell, G D; Hallgren, Björn I; Ilie, S; Kersten, S; Kind, P; Langedrag, K; Lindsay, S; Merkel, M; Stapnes, Steinar; Thadome, J; Vacek, V

    2000-01-01

    We report on the development of evaporative fluorocarbon cooling recirculators and their control systems for the ATLAS inner silicon tracker. We have developed a prototype circulator using a dry, hermetic compressor with C/sub 3/F/sup 8/ refrigerant, and have prototyped the remote-control analog pneumatic links for the regulation of coolant mass flows and operating temperatures that will be necessary in the magnetic field and radiation environment around ATLAS. pressure and flow measurement and control use 150+ channels of standard ATLAS LMB ("Local Monitor Board") DAQ and DACs on a multi-drop CAN network administered through a BridgeVIEW user interface. A hardwired thermal interlock system has been developed to cut power to individual silicon modules should their temperatures exceed safe values. Highly satisfactory performance of the circulator under steady state, partial-load and transient conditions was seen, with proportional fluid flow tuned to varying circuit power. Future developments, including a 6 kW...

  9. Preparing a new book on ATLAS

    CERN Multimedia

    Claudia Marcelloni de Oliveira

    A book about the ATLAS project and the ATLAS collaboration is going to be published and available for sale in mid 2008. The book is intended to be a symbol of appreciation for all the people from ATLAS institutes, triggering fond memories through photos, interviews, short commentaries and anecdotes about the daily life and milestones encountered while designing, constructing and completing ATLAS. We would like to give you the opportunity to collaborate with this project in two different ways: Firstly, please send us the best anecdotes related to ATLAS that you remember. To submit anecdotes, send an email to Claudia.Marcelloni@cern.ch. Secondly, you are invited to participate in our PHOTO COMPETITION. Please send the best photos you have of ATLAS attached with a description, the location, and date taken. The categories are: Milestones in the process of designing and building the detector, People at work and Important gatherings. To submit photos you should go to the CDS page and select ATLAS Photo Competi...

  10. ATLAS B-physics potential

    International Nuclear Information System (INIS)

    Smizanska, M.

    2001-01-01

    Studies since 1993 have demonstrated the ability of ATLAS to pursue a wide B physics program. This document presents the latest performance studies with special stress on lepton identification. B-decays containing several leptons in ATLAS statistically dominate the high-precision measurements. We present new results on physics simulations of CP violation measurements in the B s 0 → J/Ψphi decay and on a novel ATLAS programme on beauty production in central proton-proton collisions of LHC

  11. Role Based Access Control system in the ATLAS experiment

    CERN Document Server

    Valsan, M L; The ATLAS collaboration; Lehmann Miotto, G; Scannicchio, D A; Schlenker, S; Filimonov, V; Khomoutnikov, V; Dumitru, I; Zaytsev, A S; Korol, A A; Bogdantchikov, A; Caramarcu, C; Ballestrero, S; Darlea, G L; Twomey, M; Bujor, F; Avolio, G

    2011-01-01

    The complexity of the ATLAS experiment motivated the deployment of an integrated Access Control System in order to guarantee safe and optimal access for a large number of users to the various software and hardware resources. Such an integrated system was foreseen since the design of the infrastructure and is now central to the operations model. In order to cope with the ever growing needs of restricting access to all resources used within the experiment, the Roles Based Access Control (RBAC) previously developed has been extended and improved. The paper starts with a short presentation of the RBAC design, implementation and the changes made to the system to allow the management and usage of roles to control access to the vast and diverse set of resources. The paper continues with a detailed description of the integration across all areas of the system: local Linux and Windows nodes in the ATLAS Control Network (ATCN), the Linux application gateways offering remote access inside ATCN, the Windows Terminal Serv...

  12. Role Based Access Control System in the ATLAS Experiment

    CERN Document Server

    Valsan, M L; The ATLAS collaboration; Lehmann Miotto, G; Scannicchio, D A; Schlenker, S; Filimonov, V; Khomoutnikov, V; Dumitru, I; Zaytsev, A S; Korol, A A; Bogdantchikov, A; Avolio, G; Caramarcu, C; Ballestrero, S; Darlea, G L; Twomey, M; Bujor, F

    2010-01-01

    The complexity of the ATLAS experiment motivated the deployment of an integrated Access Control System in order to guarantee safe and optimal access for a large number of users to the various software and hardware resources. Such an integrated system was foreseen since the design of the infrastructure and is now central to the operations model. In order to cope with the ever growing needs of restricting access to all resources used within the experiment, the Roles Based Access Control (RBAC) previously developed has been extended and improved. The paper starts with a short presentation of the RBAC design, implementation and the changes made to the system to allow the management and usage of roles to control access to the vast and diverse set of resources. The paper continues with a detailed description of the integration across all areas of the system: local Linux and Windows nodes in the ATLAS Control Network (ATCN), the Linux application gateways offering remote access inside ATCN, the Windows Terminal Serv...

  13. ATLAS Award for Shield Supplier

    CERN Multimedia

    2004-01-01

    ATLAS technical coordinator Dr. Marzio Nessi presents the ATLAS supplier award to Vojtech Novotny, Director General of Skoda Hute.On 3 November, the ATLAS experiment honoured one of its suppliers, Skoda Hute s.r.o., of Plzen, Czech Republic, for their work on the detector's forward shielding elements. These huge and very massive cylinders surround the beampipe at either end of the detector to block stray particles from interfering with the ATLAS's muon chambers. For the shields, Skoda Hute produced 10 cast iron pieces with a total weight of 780 tonnes at a cost of 1.4 million CHF. Although there are many iron foundries in the CERN member states, there are only a limited number that can produce castings of the necessary size: the large pieces range in weight from 59 to 89 tonnes and are up to 1.5 metres thick.The forward shielding was designed by the ATLAS Technical Coordination in close collaboration with the ATLAS groups from the Czech Technical University and Charles University in Prague. The Czech groups a...

  14. ATLAS Facility Description Report

    International Nuclear Information System (INIS)

    Kang, Kyoung Ho; Moon, Sang Ki; Park, Hyun Sik; Cho, Seok; Choi, Ki Yong

    2009-04-01

    A thermal-hydraulic integral effect test facility, ATLAS (Advanced Thermal-hydraulic Test Loop for Accident Simulation), has been constructed at KAERI (Korea Atomic Energy Research Institute). The ATLAS has the same two-loop features as the APR1400 and is designed according to the well-known scaling method suggested by Ishii and Kataoka to simulate the various test scenarios as realistically as possible. It is a half-height and 1/288-volume scaled test facility with respect to the APR1400. The fluid system of the ATLAS consists of a primary system, a secondary system, a safety injection system, a break simulating system, a containment simulating system, and auxiliary systems. The primary system includes a reactor vessel, two hot legs, four cold legs, a pressurizer, four reactor coolant pumps, and two steam generators. The secondary system of the ATLAS is simplified to be of a circulating loop-type. Most of the safety injection features of the APR1400 and the OPR1000 are incorporated into the safety injection system of the ATLAS. In the ATLAS test facility, about 1300 instrumentations are installed to precisely investigate the thermal-hydraulic behavior in simulation of the various test scenarios. This report describes the scaling methodology, the geometric data of the individual component, and the specification and the location of the instrumentations in detail

  15. TU-CD-BRA-05: Atlas Selection for Multi-Atlas-Based Image Segmentation Using Surrogate Modeling

    International Nuclear Information System (INIS)

    Zhao, T; Ruan, D

    2015-01-01

    Purpose: The growing size and heterogeneity in training atlas necessitates sophisticated schemes to identify only the most relevant atlases for the specific multi-atlas-based image segmentation problem. This study aims to develop a model to infer the inaccessible oracle geometric relevance metric from surrogate image similarity metrics, and based on such model, provide guidance to atlas selection in multi-atlas-based image segmentation. Methods: We relate the oracle geometric relevance metric in label space to the surrogate metric in image space, by a monotonically non-decreasing function with additive random perturbations. Subsequently, a surrogate’s ability to prognosticate the oracle order for atlas subset selection is quantified probabilistically. Finally, important insights and guidance are provided for the design of fusion set size, balancing the competing demands to include the most relevant atlases and to exclude the most irrelevant ones. A systematic solution is derived based on an optimization framework. Model verification and performance assessment is performed based on clinical prostate MR images. Results: The proposed surrogate model was exemplified by a linear map with normally distributed perturbation, and verified with several commonly-used surrogates, including MSD, NCC and (N)MI. The derived behaviors of different surrogates in atlas selection and their corresponding performance in ultimate label estimate were validated. The performance of NCC and (N)MI was similarly superior to MSD, with a 10% higher atlas selection probability and a segmentation performance increase in DSC by 0.10 with the first and third quartiles of (0.83, 0.89), compared to (0.81, 0.89). The derived optimal fusion set size, valued at 7/8/8/7 for MSD/NCC/MI/NMI, agreed well with the appropriate range [4, 9] from empirical observation. Conclusion: This work has developed an efficacious probabilistic model to characterize the image-based surrogate metric on atlas selection

  16. ATLAS computing on Swiss Cloud SWITCHengines

    Science.gov (United States)

    Haug, S.; Sciacca, F. G.; ATLAS Collaboration

    2017-10-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

  17. ATLAS computing on Swiss Cloud SWITCHengines

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00215485; The ATLAS collaboration; Sciacca, Gianfranco

    2017-01-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

  18. Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

    Directory of Open Access Journals (Sweden)

    Kishan Andre Liyanage

    Full Text Available Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap to 1 (complete overlap. For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

  19. Taking ATLAS to new heights

    CERN Document Server

    Abha Eli Phoboo, ATLAS experiment

    2013-01-01

    Earlier this month, 51 members of the ATLAS collaboration trekked up to the highest peak in the Atlas Mountains, Mt. Toubkal (4,167m), in North Africa.    The physicists were in Marrakech, Morocco, attending the ATLAS Overview Week (7 - 11 October), which was held for the first time on the African continent. Around 300 members of the collaboration met to discuss the status of the LS1 upgrades and plans for the next run of the LHC. Besides the trek, 42 ATLAS members explored the Saharan sand dunes of Morocco on camels.  Photos courtesy of Patrick Jussel.

  20. Videoconferencing using workstations in the ATLAS collaboration

    International Nuclear Information System (INIS)

    Onions, C.; Blokzijl, K. Bos

    1994-01-01

    The ATLAS collaboration consists of about 1000 physicists from close to 100 institutes around the world. This number is expected to grow over the coming years. The authors realized that they needed to do something to allow people to participate in meetings held at CERN without having to travel and hence they started a pilot project in July, 1993 to look into this. Colleagues from Nikhef already had experience of international network meetings (e.g. RIPE) using standard UNIX workstations and public domain software tools using the MBONE, hence they investigated this as a first priority

  1. ATLAS Computing on the Swiss Cloud SWITCHengines

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00215485; The ATLAS collaboration; Sciacca, Gianfranco

    2016-01-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performance used and achieved running ATLAS production on SWITCHengines. SWITCHengines is the new cloud infrastructure offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, which we also report on, are country specific.

  2. Brief retrospection on Hungarian school atlases

    Science.gov (United States)

    Klinghammer, István; Jesús Reyes Nuñez, José

    2018-05-01

    The first part of this article is dedicated to the history of Hungarian school atlases to the end of the 1st World War. Although the first maps included in a Hungarian textbook were probably made in 1751, the publication of atlases for schools is dated almost 50 years later, when professor Ézsáiás Budai created his "New School Atlas for elementary pupils" in 1800. This was followed by a long period of 90 years, when the school atlases were mostly translations and adaptations of foreign atlases, the majority of which were made in German-speaking countries. In those years, a school atlas made by a Hungarian astronomer, Antal Vállas, should be highlighted as a prominent independent piece of work. In 1890, a talented cartographer, Manó Kogutowicz founded the Hungarian Geographical Institute, which was the institution responsible for producing school atlases for the different types of schools in Hungary. The professional quality of the school atlases published by his institute was also recognized beyond the Hungarian borders by prizes won in international exhibitions. Kogutowicz laid the foundations of the current Hungarian school cartography: this statement is confirmed in the second part of this article, when three of his school atlases are presented in more detail to give examples of how the pupils were introduced to the basic cartographic and astronomic concepts as well as how different innovative solutions were used on the maps.

  3. ATLAS Maintenance and Operation management system

    CERN Document Server

    Copy, B

    2007-01-01

    The maintenance and operation of the ATLAS detector will involve thousands of contributors from 170 physics institutes. Planning and coordinating the action of ATLAS members, ensuring their expertise is properly leveraged and that no parts of the detector are understaffed or overstaffed will be a challenging task. The ATLAS Maintenance and Operation application (referred to as Operation Task Planner inside the ATLAS experiment) offers a fluent web based interface that combines the flexibility and comfort of a desktop application, intuitive data visualization and navigation techniques, with a lightweight service oriented architecture. We will review the application, its usage within the ATLAS experiment, its underlying design and implementation.

  4. Popularity Prediction Tool for ATLAS Distributed Data Management

    CERN Document Server

    Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2013-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

  5. Popularity Prediction Tool for ATLAS Distributed Data Management

    CERN Document Server

    Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2014-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

  6. Taus at ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Demers, Sarah M. [Yale Univ., New Haven, CT (United States). Dept. of Physics

    2017-12-06

    The grant "Taus at ATLAS" supported the group of Sarah Demers at Yale University over a period of 8.5 months, bridging the time between her Early Career Award and her inclusion on Yale's grant cycle within the Department of Energy's Office of Science. The work supported the functioning of the ATLAS Experiment at CERN's Large Hadron Collider and the analysis of ATLAS data. The work included searching for the Higgs Boson in a particular mode of its production (with a W or Z boson) and decay (to a pair of tau leptons.) This was part of a broad program of characterizing the Higgs boson as we try to understand this recently discovered particle, and whether or not it matches our expectations within the current standard model of particle physics. In addition, group members worked with simulation to understand the physics reach of planned upgrades to the ATLAS experiment. Supported group members include postdoctoral researcher Lotte Thomsen and graduate student Mariel Pettee.

  7. Soft QCD at CMS and ATLAS

    CERN Document Server

    Starovoitov, Pavel; The ATLAS collaboration

    2018-01-01

    A short overview of the recent soft QCD results from the ATLAS and CMS collaborations is presented. The inelastic cross section measurement by CMS at 13 TeV is summarised. The contribution of the diffractive processes to the very forward photon spectra studied by ATLAS and LHCf is discussed. The ATLAS measurements of the exclusive two-photon production of the muon pairs is presented and compared to the previous ATLAS and CMS results.

  8. AGIS: The ATLAS Grid Information System

    OpenAIRE

    Anisenkov, Alexey; Belov, Sergey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

    2012-01-01

    ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configurat...

  9. The ATLAS trigger high-level trigger commissioning and operation during early data taking

    CERN Document Server

    Goncalo, R

    2008-01-01

    The ATLAS experiment is one of the two general-purpose experiments due to start operation soon at the Large Hadron Collider (LHC). The LHC will collide protons at a centre of mass energy of 14~TeV, with a bunch-crossing rate of 40~MHz. The ATLAS three-level trigger will reduce this input rate to match the foreseen offline storage capability of 100-200~Hz. After the Level 1 trigger, which is implemented in custom hardware, the High-Level Trigger (HLT) further reduces the rate from up to 100~kHz to the offline storage rate while retaining the most interesting physics. The HLT is implemented in software running in commercially available computer farms and consists of Level 2 and Event Filter. To reduce the network data traffic and the processing time to manageable levels, the HLT uses seeded, step-wise reconstruction, aiming at the earliest possible rejection. Data produced during LHC commissioning will be vital for calibrating and aligning sub-detectors, as well as for testing the ATLAS trigger and setting up t...

  10. ATLAS B-physics potential

    CERN Document Server

    Smizanska, M

    2001-01-01

    Studies since 1993 have demonstrated the ability of ATLAS to pursue a wide B physics program. This document presents the latest performance studies with special stress on lepton identification. B-decays containing several leptons in ATLAS statistically dominate the high- precision measurements. We present new results on physics simulations of CP violation measurements in the B/sub s//sup 0/ to J/ psi phi decay and on a novel ATLAS programme on beauty production in central proton-proton collisions at the LHC. (7 refs).

  11. ATLAS. LHC experiments

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    In Greek mythology, Atlas was a Titan who had to hold up the heavens with his hands as a punishment for having taken part in a revolt against the Olympians. For LHC, the ATLAS detector will also have an onerous physics burden to bear, but this is seen as a golden opportunity rather than a punishment. The major physics goal of CERN's LHC proton-proton collider is the quest for the long-awaited£higgs' mechanism which drives the spontaneous symmetry breaking of the electroweak Standard Model picture. The large ATLAS collaboration proposes a large general-purpose detector to exploit the full discovery potential of LHC's proton collisions. LHC will provide proton-proton collision luminosities at the aweinspiring level of 1034 cm2 s~1, with initial running in at 1033. The ATLAS philosophy is to handle as many signatures as possible at all luminosity levels, with the initial running providing more complex possibilities. The ATLAS concept was first presented as a Letter of Intent to the LHC Committee in November 1992. Following initial presentations at the Evian meeting (Towards the LHC Experimental Programme') in March of that year, two ideas for generalpurpose detectors, the ASCOT and EAGLE schemes, merged, with Friedrich Dydak (MPI Munich) and Peter Jenni (CERN) as ATLAS cospokesmen. Since the initial Letter of Intent presentation, the ATLAS design has been optimized and developed, guided by physics performance studies and the LHC-oriented detector R&D programme (April/May, page 3). The overall detector concept is characterized by an inner superconducting solenoid (for inner tracking) and large superconducting air-core toroids outside the calorimetry. This solution avoids constraining the calorimetry while providing a high resolution, large acceptance and robust detector. The outer magnet will extend over a length of 26 metres, with an outer diameter of almost 20 metres. The total weight of the detector is 7,000 tonnes. Fitted with its end

  12. Polyphased Inversions of an Intracontinental Rift: Case Study of the Marrakech High Atlas, Morocco

    Science.gov (United States)

    Leprêtre, R.; Missenard, Y.; Barbarand, J.; Gautheron, C.; Jouvie, I.; Saddiqi, O.

    2018-03-01

    The High and Middle Atlas intraplate belts in Morocco correspond to Mesozoic rifted basins inverted during the Cenozoic during Africa/Eurasia convergence. The Marrakech High Atlas lies at a key location between Atlantic and Tethyan influences during the Mesozoic rifting phase but represents today high reliefs. Age and style of deformation and the mechanisms underlying the Cenozoic inversion are nevertheless still debated. To solve this issue, we produced new low-temperature thermochronology data (fission track and [U-Th]/He on apatite). Two cross sections were investigated in the western and eastern Marrakech High Atlas. Results of inverse modeling allow recognizing five cooling events attributed to erosion since Early Jurassic. Apart from a first erosional event from Middle/Late Jurassic to Early Cretaceous, four stages can be related to the convergence processes between Africa and Europe since the Late Cretaceous. Our data and thermal modeling results suggest that the inversion processes are guided at first order by the fault network inherited from the rifting episodes. The sedimentary cover and the Neogene lithospheric thinning produced a significant thermal weakening that facilitated the inversion of this ancient rift. Our data show that the Marrakech High Atlas has been behaving as a giant pop-up since the beginning of Cenozoic inversion stages.

  13. ATLAS Distributed Computing in LHC Run2

    International Nuclear Information System (INIS)

    Campana, Simone

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run-2. An increase in both the data rate and the computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (Prodsys-2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward a flexible computing model. A flexible computing utilization exploring the use of opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model; the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover, a new data management strategy, based on a defined lifetime for each dataset, has been defined to better manage the lifecycle of the data. In this note, an overview of an operational experience of the new system and its evolution is presented. (paper)

  14. Evolution of the open-source data management system Rucio for LHC Run-3 and beyond ATLAS

    CERN Document Server

    Barisits, Martin-Stefan; The ATLAS collaboration

    2018-01-01

    Rucio, the distributed data management system of the ATLAS collaboration already manages more than 330 Petabytes of physics data on the grid. Rucio has seen incremental improvements throughout LHC Run-2 and is currently being prepared for the HL-LHC era of the experiment. Next to these improvements the system is currently evolving into a full-scale generic data management system for application beyond ATLAS, or even beyond high energy physics. This contribution focuses on the development roadmap of Rucio for LHC Run-3, such as, event level data management, generic meta-data support, and increased usage of networks and tapes. At the same time Rucio is evolving beyond the original ATLAS use-case. This includes authentication beyond the WLCG ecosystem, generic database compatibility, deployment and packaging of the software stack in containers and a project paradigm shift to a full-scale open source project.

  15. Increasing Drought Sensitivity and Decline of Atlas Cedar (Cedrus atlantica in the Moroccan Middle Atlas Forests

    Directory of Open Access Journals (Sweden)

    Jesús Julio Camarero

    2011-09-01

    Full Text Available An understanding of the interactions between climate change and forest structure on tree growth are needed for decision making in forest conservation and management. In this paper, we investigated the relative contribution of tree features and stand structure on Atlas cedar (Cedrus atlantica radial growth in forests that have experienced heavy grazing and logging in the past. Dendrochronological methods were applied to quantify patterns in basal-area increment and drought sensitivity of Atlas cedar in the Middle Atlas, northern Morocco. We estimated the tree-to-tree competition intensity and quantified the structure in Atlas cedar stands with contrasting tree density, age, and decline symptoms. The relative contribution of tree age and size and stand structure to Atlas cedar growth decline was estimated by variance partitioning using partial-redundancy analyses. Recurrent drought events and temperature increases have been identified from local climate records since the 1970s. We detected consistent growth declines and increased drought sensitivity in Atlas cedar across all sites since the early 1980s. Specifically, we determined that previous growth rates and tree age were the strongest tree features, while Quercus rotundifolia basal area was the strongest stand structure measure related to Atlas cedar decline. As a result, we suggest that Atlas cedar forests that have experienced severe drought in combination with grazing and logging may be in the process of shifting dominance toward more drought-tolerant species such as Q. rotundifolia.

  16. ATLAS End-cap Part II

    CERN Multimedia

    2007-01-01

    The epic journey of the ATLAS magnets is drawing to an end. On Thursday 12 July, the second end-cap of the ATLAS toroid magnet was lowered into the cavern of the experiment with the same degree of precision as the first (see Bulletin No. 26/2007). This spectacular descent of the 240-tonne component, is one of the last transport to be completed for ATLAS.

  17. ATLAS experiment : mapping the secrets of the universe

    CERN Multimedia

    ATLAS Outreach

    2010-01-01

    This 4 page color brochure describes ATLAS and the LHC, the ATLAS inner detector, calorimeters, muon spectrometer, magnet system, a short definition of the terms "particles," "dark matter," "mass," "antimatter." It also explains the ATLAS collaboration and provides the ATLAS website address with some images of the detector and the ATLAS collaboration at work.

  18. Mindboggle: Automated brain labeling with multiple atlases

    International Nuclear Information System (INIS)

    Klein, Arno; Mensh, Brett; Ghosh, Satrajit; Tourville, Jason; Hirsch, Joy

    2005-01-01

    To make inferences about brain structures or activity across multiple individuals, one first needs to determine the structural correspondences across their image data. We have recently developed Mindboggle as a fully automated, feature-matching approach to assign anatomical labels to cortical structures and activity in human brain MRI data. Label assignment is based on structural correspondences between labeled atlases and unlabeled image data, where an atlas consists of a set of labels manually assigned to a single brain image. In the present work, we study the influence of using variable numbers of individual atlases to nonlinearly label human brain image data. Each brain image voxel of each of 20 human subjects is assigned a label by each of the remaining 19 atlases using Mindboggle. The most common label is selected and is given a confidence rating based on the number of atlases that assigned that label. The automatically assigned labels for each subject brain are compared with the manual labels for that subject (its atlas). Unlike recent approaches that transform subject data to a labeled, probabilistic atlas space (constructed from a database of atlases), Mindboggle labels a subject by each atlas in a database independently. When Mindboggle labels a human subject's brain image with at least four atlases, the resulting label agreement with coregistered manual labels is significantly higher than when only a single atlas is used. Different numbers of atlases provide significantly higher label agreements for individual brain regions. Increasing the number of reference brains used to automatically label a human subject brain improves labeling accuracy with respect to manually assigned labels. Mindboggle software can provide confidence measures for labels based on probabilistic assignment of labels and could be applied to large databases of brain images

  19. ATLAS Visitors Centre

    CERN Multimedia

    claudia Marcelloni

    2009-01-01

    ATLAS Visitors Centre has opened its shiny new doors to the public. Officially launched on Monday February 23rd, 2009, the permanent exhibition at Point 1 was conceived as a tour resource for ATLAS guides, and as a way to preserve the public’s opportunity to get a close-up look at the experiment in action when the cavern is sealed.

  20. ATLAS rewards industry

    CERN Document Server

    Maximilien Brice

    2006-01-01

    For contributing vital pieces to the ATLAS puzzle, three industries were recognized on Friday 5 May during a supplier awards ceremony. After a welcome and overview of the ATLAS experiment by spokesperson Peter Jenni, CERN Secretary-General Maximilian Metzger stressed the importance of industry to CERN's scientific goals. Picture 30 : representatives of the three award-wining companies after the ceremony

  1. Online Particle Detection by Neural Networks Based on Topologic Calorimetry Information

    CERN Document Server

    Ciodaro, T; The ATLAS collaboration; Damazio, D; de Seixas, JM

    2011-01-01

    This paper presents the last results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction over the ATLAS calorimetry information (energy measurements). Later, the extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time in 59%. Also, the payload necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount

  2. The ATLAS Experiment Laboratory - Overview

    International Nuclear Information System (INIS)

    Malecki, P.

    1999-01-01

    Full text: ATLAS Experiment Laboratory has been created by physicists and engineers preparing a research programme and detector for the LHC collider. This group is greatly supported by members of other Departments taking also part (often full time) in the ATLAS project. These are: J. Blocki, J. Godlewski, Z. Hajduk, P. Kapusta, B. Kisielewski, W. Ostrowicz, E. Richter-Was, and M. Turala. Our ATLAS Laboratory realizes its programme in very close collaboration with the Faculty of Physics and Nuclear Technology of the University of Mining and Metallurgy. ATLAS, A Toroidal LHC ApparatuS Collaboration groups about 1700 experimentalists from about 150 research institutes. This apparatus, a huge system of many detectors, which are technologically very advanced, is going to be ready by 2005. With the start of the 2 x 7 TeV LHC collider ATLAS and CMS (the sister experiment at LHC) will begin their fascinating research programme at beam energies and intensities which have never been exploited. (author)

  3. ATLAS Award for Difficult Task

    CERN Multimedia

    2004-01-01

    Two Russian companies were honoured with an ATLAS Award, for supply of the ATLAS Inner Detector barrel support structure elements, last week. On 23 March the Russian company ORPE Technologiya and its subcontractor, RSP Khrunitchev, were jointly presented with an ATLAS Supplier Award. Since 1998, ORPE Technologiya has been actively involved in the development of the carbon-fibre reinforced plastic elements of the ATLAS Inner Detector barrel support structure. After three years of joint research and development, CERN and ORPE Technologiya launched the manufacturing contract. It had a tight delivery schedule and very demanding specifications in terms of mechanical tolerance and stability. The contract was successfully completed with the arrival of the last element of the structure at CERN on 8 January 2004. The delivery of this key component of the Inner Detector deserves an ATLAS Award given the difficulty of manufacturing the end-frames, which very few companies in the world would have been able to do at an ...

  4. ATLAS & Google - The Data Ocean Project

    CERN Document Server

    Lassnig, Mario; The ATLAS collaboration

    2018-01-01

    With the LHC High Luminosity upgrade the workload and data management systems are facing new major challenges. To address those challenges ATLAS and Google agreed to cooperate on a project to connect Google Cloud Storage and Compute Engine to the ATLAS computing environment. The idea is to allow ATLAS to explore the use of different computing models, to allow ATLAS user analysis to benefit from the Google infrastructure, and to give Google real science use cases to improve their cloud platform. Making the output of a distributed analysis from the grid quickly available to the analyst is a difficult problem. Redirecting the analysis output to Google Cloud Storage can provide an alternative, faster solution for the analyst. First, Google's Cloud Storage will be connected to the ATLAS Data Management System Rucio. The second part aims to let jobs run on Google Compute Engine, accessing data from either ATLAS storage or Google Cloud Storage. The third part involves Google implementing a global redirection between...

  5. The ATLAS hadronic tau trigger

    International Nuclear Information System (INIS)

    Shamim, Mansoora

    2012-01-01

    The extensive tau physics programs of the ATLAS experiment relies heavily on trigger to select hadronic decays of tau lepton. Such a trigger is implemented in ATLAS to efficiently collect signal events, while keeping the rate of multi-jet background within the allowed bandwidth. This contribution summarizes the performance of the ATLAS hadronic tau trigger system during 2011 data taking period and improvements implemented for the 2012 data collection.

  6. Short wavelength lateral variability of lithospheric mantle beneath the Middle Atlas (Morocco) as recorded by mantle xenoliths

    Science.gov (United States)

    El Messbahi, Hicham; Bodinier, Jean-Louis; Vauchez, Alain; Dautria, Jean-Marie; Ouali, Houssa; Garrido, Carlos J.

    2015-05-01

    The Middle Atlas is a region where xenolith-bearing volcanism roughly coincides with the maximum of lithospheric thinning beneath continental Morocco. It is therefore a key area to study the mechanisms of lithospheric thinning and constrain the component of mantle buoyancy that is required to explain the Moroccan topography. Samples from the two main xenolith localities, the Bou Ibalghatene and Tafraoute maars, have been investigated for their mineralogy, microstructures, crystallographic preferred orientation, and whole-rock and mineral compositions. While Bou Ibalghatene belongs to the main Middle Atlas volcanic field, in the 'tabular' Middle Atlas, Tafraoute is situated about 45 km away, on the North Middle Atlas Fault that separates the 'folded' Middle Atlas, to the South-East, from the 'tabular' Middle Atlas, to the North-West. Both xenolith suites record infiltration of sub-lithospheric melts that are akin to the Middle Atlas volcanism but were differentiated to variable degrees as a result of interactions with lithospheric mantle. However, while the Bou Ibalghatene mantle was densely traversed by high melt fractions, mostly focused in melt conduits, the Tafraoute suite records heterogeneous infiltration of smaller melt fractions that migrated diffusively, by intergranular porous flow. As a consequence the lithospheric mantle beneath Bou Ibalghaten was strongly modified by melt-rock interactions in the Cenozoic whereas the Tafraoute mantle preserves the record of extensional lithospheric thinning, most likely related to Mesozoic rifting. The two xenolith suites illustrate distinct mechanisms of lithospheric thinning: extensional thinning in Tafraoute, where hydrous incongruent melting triggered by decompression probably played a key role in favouring strain localisation, vs. thermal erosion in Bou Ibalghatene, favoured and guided by a dense network of melt conduits. Our results lend support to the suggestion that lithospheric thinning beneath the Atlas

  7. ATLAS OF EUROPEAN VALUES

    NARCIS (Netherlands)

    M Ed Uwe Krause

    2008-01-01

    Uwe Krause: Atlas of Eurpean Values De Atlas of European Values is een samenwerkingsproject met bijbehorende website van de Universiteit van Tilburg en Fontys Lerarenopleiding in Tilburg, waarbij de wetenschappelijke data van de European Values Study (EVS) voor het onderwijs toegankelijk worden

  8. ATLAS brochure (Italian version)

    CERN Multimedia

    Lefevre, C

    2010-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  9. ATLAS brochure (French version)

    CERN Multimedia

    Lefevre, C

    2012-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  10. ATLAS brochure (German version)

    CERN Multimedia

    Lefevre, C

    2012-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  11. ATLAS brochure (Danish version)

    CERN Multimedia

    Lefevre, C

    2010-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  12. The Hatfield SCT lunar atlas photographic atlas for Meade, Celestron, and other SCT telescopes

    CERN Document Server

    2014-01-01

    In a major publishing event for lunar observers, the justly famous Hatfield atlas is updated in even more usable form. This version of Hatfield’s classic atlas solves the problem of mirror images, making identification of left-right reversed imaged lunar features both quick and easy. SCT and Maksutov telescopes – which of course include the best-selling models from Meade and Celestron – reverse the visual image left to right. Thus it is extremely difficult to identify lunar features at the eyepiece of one of the instruments using a conventional Moon atlas, as the human brain does not cope well when trying to compare the real thing with a map that is a mirror image of it. Now this issue has at last been solved.   In this atlas the Moon’s surface is shown at various sun angles, and inset keys show the effects of optical librations. Smaller non-mirrored reference images are also included to make it simple to compare the mirrored SCT plates and maps with those that appear in other atlases. This edition s...

  13. Last piece of the puzzle for ATLAS

    CERN Multimedia

    Clare Ryan

    At around 15.40 on Friday 29th February the ATLAS collaboration cracked open the champagne as the second of the small wheels was lowered into the cavern. Each of ATLAS' small wheels are 9.3 metres in diameter and weigh 100 tonnes including the massive shielding elements. They are the final parts of ATLAS' muon spectrometer. The first piece of ATLAS was installed in 2003 and since then many detector elements have journeyed down the 100 metre shaft into the ATLAS underground cavern. This last piece completes this gigantic puzzle.

  14. NATIONAL ATLAS OF THE ARCTIC

    Directory of Open Access Journals (Sweden)

    Nikolay S. Kasimov

    2018-01-01

    Full Text Available The National Atlas of the Arctic is a set of spatio-temporal information about the geographic, ecological, economic, historical-ethnographic, cultural, and social features of theArcticcompiled as a cartographic model of the territory. The Atlas is intended for use in a wide range of scientific, management, economic, defense, educational, and public activities. The state policy of theRussian Federationin the Arctic for the period until 2020 and beyond, states that the Arctic is of strategic importance forRussiain the 21st century. A detailed description of all sections of the Atlas is given. The Atlas can be used as an information-reference and educational resource or as a gift edition.

  15. PanDA Beyond ATLAS: Workload Management for Data Intensive Science

    CERN Document Server

    Schovancova, J; The ATLAS collaboration; Klimentov, A; Maeno, T; Nilsson, P; Oleynik, D; Panitkin, S; Petrosyan, A; Vaniachine, A; Wenaus, T; Yu, D

    2013-01-01

    The PanDA Production ANd Distributed Analysis system has been developed by ATLAS to meet the experiment's requirements for a data-driven workload management system for production and distributed analysis processing capable of operating at LHC data processing scale. After 7 years of impressively successful PanDA operation in ATLAS there are also other experiments which can benefit from PanDA in the Big Data challenge, with several at various stages of evaluation and adoption. The new project "Next Generation Workload Management and Analysis System for Big Data" is extending PanDA to meet the needs of other data intensive scientific applications in HEP, astro-particle and astrophysics communities, bio-informatics and other fields as a general solution to large scale workload management. PanDA can utilize dedicated or opportunistic computing resources such as grids, clouds, and High Performance Computing facilities, and is being extended to leverage next generation intelligent networks in automated workflow mana...

  16. The ATLAS Event Service: A New Approach to Event Processing

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00070566; De, Kaushik; Guan, Wen; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Panitkin, Sergey; Tsulaia, Vakhtang; van Gemmeren, Peter; Wenaus, Torre

    2015-01-01

    The ATLAS Event Service (ES) implements a new fine grained approach to HEP event processing, designed to be agile and efficient in exploiting transient, short-lived resources such as HPC hole-filling, spot market commercial clouds, and volunteer computing. Input and output control and data flows, bookkeeping, monitoring, and data storage are all managed at the event level in an implementation capable of supporting ATLAS-scale distributed processing throughputs (about 4M CPU-hours/day). Input data flows utilize remote data repositories with no data locality or pre­staging requirements, minimizing the use of costly storage in favor of strongly leveraging powerful networks. Object stores provide a highly scalable means of remotely storing the quasi-continuous, fine grained outputs that give ES based applications a very light data footprint on a processing resource, and ensure negligible losses should the resource suddenly vanish. We will describe the motivations for the ES system, its unique features and capabi...

  17. EnviroAtlas Proximity to Parks Web Service

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This EnviroAtlas dataset shows...

  18. Fully convolutional neural networks improve abdominal organ segmentation

    Science.gov (United States)

    Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

    2018-03-01

    Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

  19. Deep Learning in Flavour Tagging at the ATLAS experiment

    CERN Document Server

    Lanfermann, Marie Christine; The ATLAS collaboration

    2017-01-01

    A novel higher-level flavour tagging algorithm called DL1 has been developed using a neural network at the ATLAS experiment at the CERN Large Hadron Collider. We have investigated the potential of Deep Learning in flavour tagging using inputs from lower-level taggers. A systematic grid search over architectures and the training hyperparameter space is presented. In this novel neural network approach, the training is performed on multiple output nodes, which provides a highly flexible tagger. The DL1 studies presented show that the obtained neural network improves discrimination against both $light-flavour$-jets and $c$-jets, and also provides a better performing $c$-tagger. The performance for arbitrary background mixtures can be adjusted after the training according to the to the needs of the physics analysis. The resulting DL1 tagger is described and a detailed set of performance plots presented, obtained from simulated $t\\overline{t}$ events at $\\sqrt(s)$=13 TeV and the Run-2 data taking conditions where t...

  20. FELIX: the new detector interface for the ATLAS experiment

    CERN Document Server

    Wu, Weihao; The ATLAS collaboration

    2018-01-01

    During the next major shutdown (2019-2020), the ATLAS experiment at the LHC at CERN will adopt the Front-End Link eXchange (FELIX) system as the interface between the data acquisition, detector control and TTC (Timing, Trigger and Control) systems and new or updated trigger and detector front-end electronics. FELIX will function as a router between custom serial links from front-end ASICs and FPGAs to data collection and processing components via a commodity switched network. Links may aggregate many slower links or be a single high bandwidth link. FELIX will also forward the LHC bunch-crossing clock, fixed latency trigger accepts and resets received from the TTC system to front-end electronics. The FELIX system uses commodity server technology in combination with FPGA-based PCIe I/O cards. The FELIX servers will run a software routing platform serving data to network clients. Commodity servers connected to FELIX systems via the same network will run the new Software Readout Driver (SW ROD) infrastructure for...

  1. FELIX: the New Detector Interface for the ATLAS Experiment

    CERN Document Server

    Aggarwal, Anamika; The ATLAS collaboration

    2018-01-01

    During the next major shutdown (2019-2020), the ATLAS experiment at the LHC will adopt the Front-End Link eXchange (FELIX) system as the interface between the data acquisition, detector control and TTC (Timing, Trigger and Control) systems and new or updated trigger and detector front-end electronics. FELIX will function as a router between custom serial links from front-end ASICs and FPGAs to data collection and processing components via a commodity switched network. Links may aggregate many slower links or be a single high bandwidth link. FELIX will also forward the LHC bunch-crossing clock, fixed latency trigger accepts and resets received from the TTC system to front-end electronics. The FELIX system uses commodity server technology in combination with FPGA-based PCIe I/O cards. The FELIX servers will run a software routing platform serving data to network clients. Commodity servers connected to FELIX systems via the same network will run the new Software Readout Driver (SW ROD) infrastructure for event f...

  2. Deep Learning in Flavour Tagging at the ATLAS experiment

    CERN Document Server

    Lanfermann, Marie Christine; The ATLAS collaboration

    2017-01-01

    A novel higher-level flavour tagging algorithm called DL1 has been developed using a neural network at the ATLAS experiment at the CERN Large Hadron Collider. We have investigated the potential of Deep Learning in flavour tagging using higher-level inputs from lower-level physics-motivated taggers. A systematic grid search over architectures and the training hyperparameter space is presented. In this novel neural network approach, the jet flavours are treated on an equal footing while training with multiple output nodes, which provides a highly flexible tagger. The DL1 studies presented show that the obtained neural network improves discrimination against both light-jets and c-jets, and also provides a novel c-tagging possibility. The performance for arbitrary background mixtures can be fine-tuned after the training by using iso-efficiency lines of constant signal efficiency, according to the to the needs of the physics analysis. The resulting DL1 tagger is described and a detailed set of performance plots pr...

  3. The performance of the ATLAS Inner Detector Trigger algorithms in pp collisions at the LHC

    International Nuclear Information System (INIS)

    Sutton, Mark

    2011-01-01

    The ATLAS [The ATLAS Collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, JINST 3:S08003, 2008 (2008)] Inner Detector trigger algorithms have been running online during data taking with proton-proton collisions at the Large Hadron Collider (LHC) since December 2009. Preliminary results on the performance of the algorithms in collisions at centre-of-mass energies of 900 GeV and 7 TeV, are discussed. The ATLAS trigger performs the online event selection in three stages. The Inner Detector information is used in the second and third triggering stages, referred to as Level-2 trigger (L2) and Event Filter (EF) respectively, or collectively as the High Level Trigger (HLT). The HLT runs software algorithms on large farms of commercial CPUs and is designed to reject collision events in real time, keeping the most interesting few events in every thousand. The average execution times per event at L2 and the EF are around 40 ms and 4 s respectively and the Inner Detector trigger algorithms can use only a fraction of these times. Within these times, data from interesting regions of the Inner Detector have to be read out through the network, unpacked, clustered and converted to the ATLAS global coordinates. The pattern recognition follows to identify the trajectories of charged particles (tracks), which are then used in combination with information from the other subdetectors to accept or reject events depending on whether they satisfy certain trigger signatures.

  4. Development, deployment and operations of ATLAS databases

    International Nuclear Information System (INIS)

    Vaniachine, A. V.; von der Schmitt, J. G.

    2008-01-01

    In preparation for ATLAS data taking, a coordinated shift from development towards operations has occurred in ATLAS database activities. In addition to development and commissioning activities in databases, ATLAS is active in the development and deployment (in collaboration with the WLCG 3D project) of the tools that allow the worldwide distribution and installation of databases and related datasets, as well as the actual operation of this system on ATLAS multi-grid infrastructure. We describe development and commissioning of major ATLAS database applications for online and offline. We present the first scalability test results and ramp-up schedule over the initial LHC years of operations towards the nominal year of ATLAS running, when the database storage volumes are expected to reach 6.1 TB for the Tag DB and 1.0 TB for the Conditions DB. ATLAS database applications require robust operational infrastructure for data replication between online and offline at Tier-0, and for the distribution of the offline data to Tier-1 and Tier-2 computing centers. We describe ATLAS experience with Oracle Streams and other technologies for coordinated replication of databases in the framework of the WLCG 3D services

  5. Designing, Implementing and Documenting the Atlas Networking Test-bed.

    CERN Document Server

    Martinsen, Hans Åge

    The A Toroidal LHC ApparatuS (Atlas) experiment at the Large Hadron Colider (LHC) in European Organization for Nuclear Research (CERN), Geneva is a production environment. To develop new architectures, test new equipment and evaluate new technologies a well supported test bench is needed. A new one is now being commissioned and I will take a leading role in its development, commissioning and operation. This thesis will cover the requirements, the implementation, the documentation and the approach to the different challenges in implementing the testbed. I will be joining the project in the early stages and start by following the work that my colleagues are doing and then, as I get a better understanding, more responsibility will be given to me. To be able to suggest and implement solutions I will have to understand what the requirements are and how to achieve these requirements with the given resources.

  6. ATLAS

    Data.gov (United States)

    Federal Laboratory Consortium — ATLAS is a particle physics experiment at the Large Hadron Collider at CERN, the European Organization for Nuclear Research. Scientists from Brookhaven have played...

  7. The Cerefy registered clinical brain atlas on CD-ROM. Based on the classic Talairach-Tournoux and Schaltenbrand-Wahren brain atlases. 2. ed.

    International Nuclear Information System (INIS)

    Nowinski, W.L.; Thirunavuukarasuu, A.

    2001-01-01

    This remarkable CD-ROM provides enhanced and extended versions of three world-famous Thieme atlases, (Schaltenbrand and Wahren's Atlas for Stereotaxy of the Human Brain, Talairach and Tournoux's Co-Planar Stereotaxis Atlas of the Human Brain and Referentially Oriented Cerebral MRI Anatomy). It contains the electronic atlases as well as an easy navigation system to facilitate searching for and displaying more than 525 anatomical structures. Revolutionizing the field of brain anatomy, the authors have segmented, labeled, and cross referenced all the information contained in the books, and created contours for all three atlases. The Cerefy registered Clinical Brain Atlas now allows you to electronically navigate these atlases simultaneously on axial, coronal, and sagittal planes, and enjoy the ability to: 1. Access 210 high-quality, fully segmented, and labeled atlas images with corresponding contours, 2. Display and manipulate spatially co-registered atlases, 3. Dynamically label images with structure names and descriptions, and then highlight selected structures in the atlas image, 4. Image zoom in five different levels, mensurate, search, set triplanar, get coordinates, save, and print, 5. Access on-line help, glossary, and supportive atlas materials. (orig.)

  8. ATLAS brochure (Norwegian version)

    CERN Multimedia

    Lefevre, C

    2009-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter. Français

  9. A Slice of ATLAS

    CERN Document Server

    2004-01-01

    An entire section of the ATLAS detector is being assembled at Prévessin. Since May the components have been tested using a beam from the SPS, giving the ATLAS team valuable experience of operating the detector as well as an opportunity to debug the system.

  10. The Latest from ATLAS

    CERN Multimedia

    2009-01-01

    Since November 2008, ATLAS has undertaken detailed maintenance, consolidation and repair work on the detector (see Bulletin of 20 July 2009). Today, the fraction of the detector that is operational has increased compared to last year: less than 1% of dead channels for most of the sub-systems. "We are going to start taking data this year with a detector which is even more efficient than it was last year," agrees ATLAS Spokesperson, Fabiola Gianotti. By mid-September the detector was fully closed again, and the cavern sealed. The magnet system has been operated at nominal current for extensive periods over recent months. Once the cavern was sealed, ATLAS began two weeks of combined running. Right now, subsystems are joining the run incrementally until the point where the whole detector is integrated and running as one. In the words of ATLAS Technical Coordinator, Marzio Nessi: "Now we really start physics." In parallel, the analysis ...

  11. A thermosiphon for ATLAS

    CERN Multimedia

    Rosaria Marraffino

    2013-01-01

    A new thermosiphon cooling system, designed for the ATLAS silicon detectors by CERN’s EN-CV team in collaboration with the experiment, will replace the current system in the next LHC run in 2015. Using the basic properties of density difference and making gravity do the hard work, the thermosiphon promises to be a very reliable solution that will ensure the long-term stability of the whole system.   Former compressor-based cooling system of the ATLAS inner detectors. The system is currently being replaced by the innovative thermosiphon. (Photo courtesy of Olivier Crespo-Lopez). Reliability is the major issue for the present cooling system of the ATLAS silicon detectors. The system was designed 13 years ago using a compressor-based cooling cycle. “The current cooling system uses oil-free compressors to avoid fluid pollution in the delicate parts of the silicon detectors,” says Michele Battistin, EN-CV-PJ section leader and project leader of the ATLAS thermosiphon....

  12. The High-Resolution IRAS Galaxy Atlas

    Science.gov (United States)

    Cao, Yu; Terebey, Susan; Prince, Thomas A.; Beichman, Charles A.; Oliversen, R. (Technical Monitor)

    1997-01-01

    An atlas of the Galactic plane (-4.7 deg is less than b is less than 4.7 deg), along with the molecular clouds in Orion, rho Oph, and Taurus-Auriga, has been produced at 60 and 100 microns from IRAS data. The atlas consists of resolution-enhanced co-added images with 1 min - 2 min resolution and co-added images at the native IRAS resolution. The IRAS Galaxy Atlas, together with the Dominion Radio Astrophysical Observatory H(sub I) line/21 cm continuum and FCRAO CO (1-0) Galactic plane surveys, which both have similar (approx. 1 min) resolution to the IRAS atlas, provides a powerful tool for studying the interstellar medium, star formation, and large-scale structure in our Galaxy. This paper documents the production and characteristics of the atlas.

  13. The geosystems of complex geographical atlases

    Directory of Open Access Journals (Sweden)

    Jovanović Jasmina

    2012-01-01

    Full Text Available Complex geographical atlases represent geosystems of different hierarchical rank, complexity and diversity, scale and connection. They represent a set of large number of different pieces of information about geospace. Also, they contain systematized, correlative and in the apparent form represented pieces of information about space. The degree of information revealed in the atlas is precisely explained by its content structure and the form of presentation. The quality of atlas depends on the method of visualization of data and the quality of geodata. Cartographic visualization represents cognitive process. The analysis converts geospatial data into knowledge. A complex geographical atlas represents information complex of spatial - temporal coordinated database on geosystems of different complexity and territorial scope. Each geographical atlas defines a concrete geosystem. Systemic organization (structural and contextual determines its complexity and concreteness. In complex atlases, the attributes of geosystems are modeled and pieces of information are given in systematized, graphically unique form. The atlas can be considered as a database. In composing a database, semantic analysis of data is important. The result of semantic modeling is expressed in structuring of data information, in emphasizing logic connections between phenomena and processes and in defining their classes according to the degree of similarity. Accordingly, the efficiency of research of needed pieces of information in the process of the database use is enabled. An atlas map has a special power to integrate sets of geodata and present information contents in user - friendly and understandable visual and tactile way using its visual ability. Composing an atlas by systemic cartography requires the pieces of information on concrete - defined geosystems of different hierarchical level, the application of scientific methods and making of adequate number of analytical, synthetic

  14. The ATLAS distributed analysis system

    OpenAIRE

    Legger, F.

    2014-01-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During...

  15. ATLAS brochure (Catalan version)

    CERN Multimedia

    Lefevre, C

    2008-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  16. ATLAS Brochure (french version)

    CERN Multimedia

    Marcastel, F

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  17. ATLAS brochure (Polish version)

    CERN Multimedia

    Lefevre, C

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  18. ATLAS Brochure (german version)

    CERN Multimedia

    Marcastel, F

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  19. ATLAS Brochure (english version)

    CERN Multimedia

    Marcastel, F

    2007-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  20. ATLAS Brochure (English version)

    CERN Multimedia

    Lefevre, Christiane

    2011-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  1. ATLAS brochure (Spanish version)

    CERN Multimedia

    Lefevre, C

    2008-01-01

    ATLAS is the largest detector at the LHC, the most powerful particle accelerator in the world, which will start up in 2008. ATLAS is a multi-purpose detector, designed to throw light on fundamental questions such as the origin of mass and the nature of the Universe's dark matter.

  2. TU-AB-202-10: How Effective Are Current Atlas Selection Methods for Atlas-Based Auto-Contouring in Radiotherapy Planning?

    Energy Technology Data Exchange (ETDEWEB)

    Peressutti, D; Schipaanboord, B; Kadir, T; Gooding, M [Mirada Medical Limited, Science and Medical Technology, Oxford (United Kingdom); Soest, J van; Lustberg, T; Elmpt, W van; Dekker, A [Maastricht University Medical Centre, Department of Radiation Oncology MAASTRO - GROW School for Oncology Developmental Biology, Maastricht (Netherlands)

    2016-06-15

    Purpose: To investigate the effectiveness of atlas selection methods for improving atlas-based auto-contouring in radiotherapy planning. Methods: 275 H&N clinically delineated cases were employed as an atlas database from which atlases would be selected. A further 40 previously contoured cases were used as test patients against which atlas selection could be performed and evaluated. 26 variations of selection methods proposed in the literature and used in commercial systems were investigated. Atlas selection methods comprised either global or local image similarity measures, computed after rigid or deformable registration, combined with direct atlas search or with an intermediate template image. Workflow Box (Mirada-Medical, Oxford, UK) was used for all auto-contouring. Results on brain, brainstem, parotids and spinal cord were compared to random selection, a fixed set of 10 “good” atlases, and optimal selection by an “oracle” with knowledge of the ground truth. The Dice score and the average ranking with respect to the “oracle” were employed to assess the performance of the top 10 atlases selected by each method. Results: The fixed set of “good” atlases outperformed all of the atlas-patient image similarity-based selection methods (mean Dice 0.715 c.f. 0.603 to 0.677). In general, methods based on exhaustive comparison of local similarity measures showed better average Dice scores (0.658 to 0.677) compared to the use of either template image (0.655 to 0.672) or global similarity measures (0.603 to 0.666). The performance of image-based selection methods was found to be only slightly better than a random (0.645). Dice scores given relate to the left parotid, but similar results patterns were observed for all organs. Conclusion: Intuitively, atlas selection based on the patient CT is expected to improve auto-contouring performance. However, it was found that published approaches performed marginally better than random and use of a fixed set of

  3. Report to users of ATLAS, January 1998

    International Nuclear Information System (INIS)

    Ahmad, I.; Hofman, D.

    1998-01-01

    This report is aimed at informing users about the operating schedule, user policies, and recent changes in research capabilities. It covers the following subjects: (1) status of the Argonne Tandem-Linac Accelerator System (ATLAS) accelerator; (2) the move of Gammasphere from LBNL to ANL; (3) commissioning of the CPT mass spectrometer at ATLAS; (4) highlights of recent research at ATLAS; (5) Program Advisory Committee; and (6) ATLAS User Group Executive Committee

  4. Hundreds of fridges to cool the heart of ATLAS

    CERN Multimedia

    2006-01-01

    The detectors used in the LHC experiments are packed with electronics that will register thousands of particles produced in the collisions. All this hard work will generate a lot of heat, but there are systems in place to help the electronics to cool down, not shut down. Members of the DC section team in USA15 of the ATLAS cavern, standing behind four of the compressors used in the cooling system. The inlet and outlet pipes that carry the refrigerant to the experimental hall can be seen on the left. Left to right: M. Battistin, P. Bonneau, C. Houd, P. Feraudet, F. Corbaz, J. Lethinen, P. Guglielmini, M. Ciclet, P. Tropea, S. Berry (M. Pimenta absent).An unconfirmed member of the DC section :-) in charge of a part of the perfluoropropane distribution network for the ATLAS evaporative cooling system. The next time your desktop computer crashes from overheating, spare a thought for Pierre Feraudet, a member of the Detector Cooling section (TS/CV/DC). He is in charge of constructing the cooling systems for the d...

  5. First ATLAS Events Recorded Underground

    CERN Multimedia

    Teuscher, R

    As reported in the CERN Bulletin, Issue No.30-31, 25 July 2005 The ATLAS barrel Tile calorimeter has recorded its first events underground using a cosmic ray trigger, as part of the detector commissioning programme. This is not a simulation! A cosmic ray muon recorded by the barrel Tile calorimeter of ATLAS on 21 June 2005 at 18:30. The calorimeter has three layers and a pointing geometry. The light trapezoids represent the energy deposited in the tiles of the calorimeter depicted as a thick disk. On the evening of June 21, the ATLAS detector, now being installed in the underground experimental hall UX15, reached an important psychological milestone: the barrel Tile calorimeter recorded the first cosmic ray events in the underground cavern. An estimated million cosmic muons enter the ATLAS cavern every 3 minutes, and the ATLAS team decided to make good use of some of them for the commissioning of the detector. Although only 8 of the 128 calorimeter slices ('superdrawers') were included in the trigg...

  6. ATLAS construction status

    International Nuclear Information System (INIS)

    Jenni, P.

    2006-01-01

    The ATLAS detector is being constructed at the LHC, in view of a data-taking startup in 2007. This report concentrates on the progress and the technical challenges of the detector construction, and summarizes the status of the work as of August 2004. The project is on track to allow the highly motivated ATLAS Collaboration to enter into a new exploratory domain of high-energy physics in 2007. (author)

  7. ATLAS cloud R and D

    International Nuclear Information System (INIS)

    Panitkin, Sergey; Bejar, Jose Caballero; Hover, John; Zaytsev, Alexander; Megino, Fernando Barreiro; Girolamo, Alessandro Di; Kucharczyk, Katarzyna; Llamas, Ramon Medrano; Benjamin, Doug; Gable, Ian; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Hendrix, Val; Love, Peter; Ohman, Henrik; Walker, Rodney

    2014-01-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R and D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R and D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R and D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R and D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

  8. The ATLAS Pixel Detector

    CERN Document Server

    Huegging, Fabian

    2006-06-26

    The contruction of the ATLAS Pixel Detector which is the innermost layer of the ATLAS tracking system is prgressing well. Because the pixel detector will contribute significantly to the ATLAS track and vertex reconstruction. The detector consists of identical sensor-chip-hybrid modules, arranged in three barrels in the centre and three disks on either side for the forward region. The position of the detector near the interaction point requires excellent radiation hardness, mechanical and thermal robustness, good long-term stability for all parts, combined with a low material budget. The final detector layout, new results from production modules and the status of assembly are presented.

  9. The Next Generation ATLAS Production System

    CERN Document Server

    Borodin, Mikhail; The ATLAS collaboration; Golubkov, Dmitry; Klimentov, Alexei; Maeno, Tadashi; Mashinistov, Ruslan; Vaniachine, Alexandre

    2015-01-01

    The ATLAS experiment at LHC data processing and simulation grows continuously, as more data and more use cases emerge. For data processing the ATLAS experiment adopted the data transformation approach, where software applications transform the input data into outputs. In the ATLAS production system, each data transformation is represented by a task, a collection of many jobs, dynamically submitted by the ATLAS workload management system (PanDA/JEDI) and executed on the Grid, clouds and supercomputers. Patterns in ATLAS data transformation workflows composed of many tasks provided a scalable production system framework for template definitions of the many-tasks workflows. User interface and system logic of these workflows are being implemented in the Database Engine for Tasks (DEFT). Such development required using modern computing technologies and approaches. We report technical details of this development: database implementation, server logic and Web user interface technologies.

  10. Hidden Valley Search at ATLAS

    CERN Document Server

    Verducci, M

    2011-01-01

    A number of extensions of the Standard Model result in neutral and weakly-coupled particles that decay to multi hadrons or multi leptons with macroscopic decay lengths. These particles with decay paths that can be comparable with ATLAS detector dimensions represent, from an experimental point of view, a challenge both for the trigger and for the reconstruction capabilities of the ATLAS detector. We will present a set of signature driven triggers for the ATLAS detector that target such displaced decays and evaluate their performances for some benchmark models and describe analysis strategies and limits on the production of such long-lived particles. A first estimation of the Hidden Valley trigger rates has been evaluated with 6 pb-1 of data collected at ATLAS during the data taking of 2010.

  11. The ATLAS detector simulation application

    International Nuclear Information System (INIS)

    Rimoldi, A.

    2007-01-01

    The simulation program for the ATLAS experiment at CERN is currently in a full operational mode and integrated into the ATLAS common analysis framework, Athena. The OO approach, based on GEANT4, has been interfaced within Athena and to GEANT4 using the LCG dictionaries and Python scripting. The robustness of the application was proved during the test productions since 2004. The Python interface has added the flexibility, modularity and interactivity that the simulation tool requires in order to be able to provide a common implementation of different full ATLAS simulation setups, test beams and cosmic ray applications. Generation, simulation and digitization steps were exercised for performance and robustness tests. The comparison with real data has been possible in the context of the ATLAS Combined Test Beam (2004-2005) and cosmic ray studies (2006)

  12. On characterizing population commonalities and subject variations in brain networks.

    Science.gov (United States)

    Ghanbari, Yasser; Bloy, Luke; Tunc, Birkan; Shankar, Varsha; Roberts, Timothy P L; Edgar, J Christopher; Schultz, Robert T; Verma, Ragini

    2017-05-01

    Brain networks based on resting state connectivity as well as inter-regional anatomical pathways obtained using diffusion imaging have provided insight into pathology and development. Such work has underscored the need for methods that can extract sub-networks that can accurately capture the connectivity patterns of the underlying population while simultaneously describing the variation of sub-networks at the subject level. We have designed a multi-layer graph clustering method that extracts clusters of nodes, called 'network hubs', which display higher levels of connectivity within the cluster than to the rest of the brain. The method determines an atlas of network hubs that describes the population, as well as weights that characterize subject-wise variation in terms of within- and between-hub connectivity. This lowers the dimensionality of brain networks, thereby providing a representation amenable to statistical analyses. The applicability of the proposed technique is demonstrated by extracting an atlas of network hubs for a population of typically developing controls (TDCs) as well as children with autism spectrum disorder (ASD), and using the structural and functional networks of a population to determine the subject-level variation of these hubs and their inter-connectivity. These hubs are then used to compare ASD and TDCs. Our method is generalizable to any population whose connectivity (structural or functional) can be captured via non-negative network graphs. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Popularity Prediction Tool for ATLAS Distributed Data Management

    Science.gov (United States)

    Beermann, T.; Maettig, P.; Stewart, G.; Lassnig, M.; Garonne, V.; Barisits, M.; Vigne, R.; Serfon, C.; Goossens, L.; Nairz, A.; Molfetas, A.; Atlas Collaboration

    2014-06-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

  14. Popularity prediction tool for ATLAS distributed data management

    International Nuclear Information System (INIS)

    Beermann, T; Maettig, P; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2014-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

  15. ATLAS Simulation using Real Data: Embedding and Overlay

    Science.gov (United States)

    Haas, Andrew; ATLAS Collaboration

    2017-10-01

    For some physics processes studied with the ATLAS detector, a more accurate simulation in some respects can be achieved by including real data into simulated events, with substantial potential improvements in the CPU, disk space, and memory usage of the standard simulation configuration, at the cost of significant database and networking challenges. Real proton-proton background events can be overlaid (at the detector digitization output stage) on a simulated hard-scatter process, to account for pileup background (from nearby bunch crossings), cavern background, and detector noise. A similar method is used to account for the large underlying event from heavy ion collisions, rather than directly simulating the full collision. Embedding replaces the muons found in Z→μμ decays in data with simulated taus at the same 4-momenta, thus preserving the underlying event and pileup from the original data event. In all these cases, care must be taken to exactly match detector conditions (beamspot, magnetic fields, alignments, dead sensors, etc.) between the real data event and the simulation. We will discuss the status of these overlay and embedding techniques within ATLAS software and computing.

  16. ATLAS end-cap detector

    CERN Multimedia

    Maximilien Brice

    2003-01-01

    Three scientists from the Institute of Nuclear Phyiscs at Novossibirsk with one of the end-caps of the ATLAS detector. The end-caps will be used to detect particles produced in the proton-proton collisions at the heart of the ATLAS experiment that are travelling close to the axis of the two beams.

  17. R-Hadron Search at ATLAS

    DEFF Research Database (Denmark)

    Heisterkamp, Simon Johann Franz

    In this thesis I motivate and present a search for long lived massive R-hadrons using the data collected by the ATLAS detector in 2011. Both ionisation- and time-of-ight-based methods are described. Since no signal was found, a lower limit on the mass of such particles is set. The analysis was also...... published by the ATLAS collboration in Phys.Lett.B. titled `Searches for heavy long-lived sleptons and R-Hadrons with the ATLAS detector in pp collisions at sqrt(s) = 7 TeV'....

  18. Rat brain digital stereotaxic white matter atlas with fine tract delineation in Paxinos space and its automated applications in DTI data analysis.

    Science.gov (United States)

    Liang, Shengxiang; Wu, Shang; Huang, Qi; Duan, Shaofeng; Liu, Hua; Li, Yuxiao; Zhao, Shujun; Nie, Binbin; Shan, Baoci

    2017-11-01

    To automatically analyze diffusion tensor images of the rat brain via both voxel-based and ROI-based approaches, we constructed a new white matter atlas of the rat brain with fine tracts delineation in the Paxinos and Watson space. Unlike in previous studies, we constructed a digital atlas image from the latest edition of the Paxinos and Watson. This atlas contains 111 carefully delineated white matter fibers. A white matter network of rat brain based on anatomy was constructed by locating the intersection of all these tracts and recording the nuclei on the pathway of each white matter tract. Moreover, a compatible rat brain template from DTI images was created and standardized into the atlas space. To evaluate the automated application of the atlas in DTI data analysis, a group of rats with right-side middle cerebral artery occlusion (MCAO) and those without were enrolled in this study. The voxel-based analysis result shows that the brain region showing significant declines in signal in the MCAO rats was consistent with the occlusion position. We constructed a stereotaxic white matter atlas of the rat brain with fine tract delineation and a compatible template for the data analysis of DTI images of the rat brain. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. ATLAS Thesis Awards 2015

    CERN Multimedia

    Biondi, Silvia

    2016-01-01

    Winners of the ATLAS Thesis Award were presented with certificates and glass cubes during a ceremony on Thursday 25 February. The winners also presented their work in front of members of the ATLAS Collaboration. Winners: Javier Montejo Berlingen, Barcelona (Spain), Ruth Pöttgen, Mainz (Germany), Nils Ruthmann, Freiburg (Germany), and Steven Schramm, Toronto (Canada).

  20. Renewable Energy Atlas of the United States

    Energy Technology Data Exchange (ETDEWEB)

    Kuiper, J. [Environmental Science Division; Hlava, K. [Environmental Science Division; Greenwood, H. [Environmentall Science Division; Carr, A. [Environmental Science Division

    2013-12-13

    The Renewable Energy Atlas (Atlas) of the United States is a compilation of geospatial data focused on renewable energy resources, federal land ownership, and base map reference information. This report explains how to add the Atlas to your computer and install the associated software. The report also includes: A description of each of the components of the Atlas; Lists of the Geographic Information System (GIS) database content and sources; and A brief introduction to the major renewable energy technologies. The Atlas includes the following: A GIS database organized as a set of Environmental Systems Research Institute (ESRI) ArcGIS Personal GeoDatabases, and ESRI ArcReader and ArcGIS project files providing an interactive map visualization and analysis interface.

  1. The ATLAS IBL CO2 Cooling System

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00237783; The ATLAS collaboration; Zwalinski, L.; Bortolin, C.; Vogt, S.; Godlewski, J.; Crespo-Lopez, O.; Van Overbeek, M.; Blaszcyk, T.

    2017-01-01

    The ATLAS Pixel detector has been equipped with an extra B-layer in the space obtained by a reduced beam pipe. This new pixel detector called the ATLAS Insertable B-Layer (IBL) is installed in 2014 and is operational in the current ATLAS data taking. The IBL detector is cooled with evaporative CO2 and is the first of its kind in ATLAS. The ATLAS IBL CO2 cooling system is designed for lower temperature operation (<-35⁰C) than the previous developed CO2 cooling systems in High Energy Physics experiments. The cold temperatures are required to protect the pixel sensors for the high expected radiation dose up to 550 fb^-1 integrated luminosity.

  2. The ATLAS Distributed Computing project for LHC Run-2 and beyond.

    CERN Document Server

    Di Girolamo, Alessandro; The ATLAS collaboration

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run2. An increased data rate and computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (ProdSys2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward the flexible computing model. The flexible computing utilization exploring the opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model, the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover a new data management strategy, based on defined lifetime for each dataset, has been defin...

  3. Commissioning of the ATLAS pixel detector

    International Nuclear Information System (INIS)

    Golling, Tobias

    2008-01-01

    The ATLAS pixel detector is a high precision silicon tracking device located closest to the LHC interaction point. It belongs to the first generation of its kind in a hadron collider experiment. It will provide crucial pattern recognition information and will largely determine the ability of ATLAS to precisely track particle trajectories and find secondary vertices. It was the last detector to be installed in ATLAS in June 2007, has been fully connected and tested in-situ during spring and summer 2008, and is ready for the imminent LHC turn-on. The highlights of the past and future commissioning activities of the ATLAS pixel system are presented

  4. Prime wires for ATLAS

    CERN Multimedia

    2003-01-01

    In an award ceremony on 3 September, ATLAS honoured the French company Axon Cable for its special coaxial cables, which were purpose-built for the Liquid Argon calorimeter modules. Working for CERN since the 1970s, Axon' Cable received the ATLAS supplier award last week for its contribution to the liquid argon calorimeter cables of ATLAS (LAL/Orsay, France and University of Victoria, Canada), started in 1996. Its two sets of minicoaxial cables, called harnesses "A" and "B", are designed to function in the harsh conditions in the liquid argon (at 90 Kelvin or -183°C) and under extreme radiation (up to several Mrads). The cables are mainly used for the readout of the calorimeters, and are connected to the outside world by 114 signal feedthroughs with 1920 channels each. The signal from the detectors is transmitted directly without any amplification, which imposes tight restrictions on the impedance and on the signal propagation time of the cables. Peter Jenni, ATLAS spokesperson, gives the award for best s...

  5. ATLAS solenoid operates underground

    CERN Multimedia

    2006-01-01

    A new phase for the ATLAS collaboration started with the first operation of a completed sub-system: the Central Solenoid. Teams monitoring the cooling and powering of the ATLAS solenoid in the control room. The solenoid was cooled down to 4.5 K from 17 to 23 May. The first current was established the same evening that the solenoid became cold and superconductive. 'This makes the ATLAS Central Solenoid the very first cold and superconducting magnet to be operated in the LHC underground areas!', said Takahiko Kondo, professor at KEK. Though the current was limited to 1 kA, the cool-down and powering of the solenoid was a major milestone for all of the control, cryogenic, power and vacuum systems-a milestone reached by the hard work and many long evenings invested by various teams from ATLAS, all of CERN's departments and several large and small companies. Since the Central Solenoid and the barrel liquid argon (LAr) calorimeter share the same cryostat vacuum vessel, this achievement was only possible in perfe...

  6. ATLAS DDM integration in ARC

    DEFF Research Database (Denmark)

    Behrmann, Gerd; Cameron, David; Ellert, Mattias

    2008-01-01

    The Nordic Data Grid Facility (NDGF) consists of Grid resources running ARC middleware in Denmark, Finland, Norway and Sweden. These resources serve many virtual organisations and contribute a large fraction of total worldwide resources for the ATLAS experiment, whose data is distributed and mana......The Nordic Data Grid Facility (NDGF) consists of Grid resources running ARC middleware in Denmark, Finland, Norway and Sweden. These resources serve many virtual organisations and contribute a large fraction of total worldwide resources for the ATLAS experiment, whose data is distributed...... and managed by the DQ2 software. Managing ATLAS data within NDGF and between NDGF and other Grids used by ATLAS (the Enabling Grids for E-sciencE Grid and the Open Science Grid) presents a unique challenge for several reasons. Firstly, the entry point for data, the Tier 1 centre, is physically distributed...

  7. The Future of Distributed Computing Systems in ATLAS: Boldly Venturing Beyond Grids

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2018-01-01

    The Production and Distributed Analysis system (PanDA) for the ATLAS experiment at the Large Hadron Collider has seen big changes over the past couple of years to accommodate new types of distributed computing resources: clouds, HPCs, volunteer computers and other external resources. While PanDA was originally designed for fairly homogeneous resources available through the Worldwide LHC Computing Grid, the new resources are heterogeneous, at diverse scales and with diverse interfaces. Up to a fifth of the resources available to ATLAS are of such new types and require special techniques for integration into PanDA. In this talk, we present the nature and scale of these resources. We provide an overview of the various challenges faced, spanning infrastructure, software distribution, workload requirements, scaling requirements, workflow management, data management, network provisioning, and associated software and computing facilities. We describe the strategies for integrating these heterogeneous resources into ...

  8. FELIX: a high-throughput network approach for interfacing to front end electronics for ATLAS upgrades

    NARCIS (Netherlands)

    Anderson, J.; Borga, A.; Boterenbrood, H.; Chen, H.; Chen, K.; Drake, G.; Francis, D.; Gorini, B.; Lanni, F.; Lehmann Miotto, G.; Levinson, L.; Narevicius, J.; Plessl, C.; Roich, A.; Ryu, S.; Schreuder, F.; Schumacher, J.; Vandelli, W.; Vermeulen, J.; Zhang, J.

    2015-01-01

    The ATLAS experiment at CERN is planning full deployment of a new unified optical link technology for connecting detector front end electronics on the timescale of the LHC Run 4 (2025). It is estimated that roughly 8000 GBT (GigaBit Transceiver) links, with transfer rates up to 10.24 Gbps, will

  9. Validating atlas-guided DOT: a comparison of diffuse optical tomography informed by atlas and subject-specific anatomies.

    Science.gov (United States)

    Cooper, Robert J; Caffini, Matteo; Dubb, Jay; Fang, Qianqian; Custo, Anna; Tsuzuki, Daisuke; Fischl, Bruce; Wells, William; Dan, Ippeita; Boas, David A

    2012-09-01

    We describe the validation of an anatomical brain atlas approach to the analysis of diffuse optical tomography (DOT). Using MRI data from 32 subjects, we compare the diffuse optical images of simulated cortical activation reconstructed using a registered atlas with those obtained using a subject's true anatomy. The error in localization of the simulated cortical activations when using a registered atlas is due to a combination of imperfect registration, anatomical differences between atlas and subject anatomies and the localization error associated with diffuse optical image reconstruction. When using a subject-specific MRI, any localization error is due to diffuse optical image reconstruction only. In this study we determine that using a registered anatomical brain atlas results in an average localization error of approximately 18 mm in Euclidean space. The corresponding error when the subject's own MRI is employed is 9.1 mm. In general, the cost of using atlas-guided DOT in place of subject-specific MRI-guided DOT is a doubling of the localization error. Our results show that despite this increase in error, reasonable anatomical localization is achievable even in cases where the subject-specific anatomy is unavailable. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. Identification of b-jets with a low pΤ muon using ATLAS Tile Calorimeter simulation data and artificial neural networks technique

    International Nuclear Information System (INIS)

    Astvatsaturov, A.; Budagov, Yu.; Shigaev, V.; Nessi, M.; Pantea, D.

    1996-01-01

    The possibility to enhance the capability of ATLAS Tile Calorimeter to identify low p Τ muons (2 Τ Τ =20 and 40 GeV/c in the central region 0 b g is 4-10 times higher in NND case compared to LTD. The results obtained are based on 2000 jets simulated with the use of ATLAS simulation programs. 8 refs., 13 figs., 2 tabs

  11. Atlas C++ Coding Standard Specification

    CERN Document Server

    Albrand, S; Barberis, D; Bosman, M; Jones, B; Stavrianakou, M; Arnault, C; Candlin, D; Candlin, R; Franck, E; Hansl-Kozanecka, Traudl; Malon, D; Qian, S; Quarrie, D; Schaffer, R D

    2001-01-01

    This document defines the ATLAS C++ coding standard, that should be adhered to when writing C++ code. It has been adapted from the original "PST Coding Standard" document (http://pst.cern.ch/HandBookWorkBook/Handbook/Programming/programming.html) CERN-UCO/1999/207. The "ATLAS standard" comprises modifications, further justification and examples for some of the rules in the original PST document. All changes were discussed in the ATLAS Offline Software Quality Control Group and feedback from the collaboration was taken into account in the "current" version.

  12. Hidden Valley Searches at ATLAS

    CERN Document Server

    Ventura, D; The ATLAS collaboration

    2011-01-01

    A number of extensions of the Standard Model result in neutral and weakly-coupled particles that decay to multi hadrons or multi leptons with macroscopic decay lengths. These particles with decay paths that can be comparable with ATLAS detector dimensions represent, from an experimental point of view, a challenge both for the trigger and for the reconstruction capabilities of the ATLAS detector. We will present a set of signature driven triggers for the ATLAS detector that target such displaced decays and evaluate their performances for some benchmark models.

  13. FELIX: the new detector readout system for the ATLAS experiment

    CERN Document Server

    Zhang, Jinlong; The ATLAS collaboration

    2017-01-01

    After the Phase-I upgrade and onward, the Front-End Link eXchange (FELIX) system will be the interface between the data handling system and the detector front-end electronics and trigger electronics at the ATLAS experiment. FELIX will function as a router between custom serial links and a commodity switch network which will use standard technologies to communicate with data collecting and processing components. The FELIX system is being developed by using commercial-off-the-shelf server PC technology in combination with a FPGA-based PCIe Gen3 I/O card interfacing to GigaBit Transceiver links and with Timing, Trigger and Control connectivity provided by an FMC-based mezzanine card. Dedicated firmware for the Xilinx FPGA (Virtex 7 and Kintex UltraScale) installed on the I/O card alongside an interrupt-driven Linux kernel driver and user-space software will provide the required functionality. On the network side, the FELIX unit connects to both Ethernet-based network and Infiniband. The system architecture of FE...

  14. EnviroAtlas Near Road Tree Buffer Web Service

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This EnviroAtlas dataset...

  15. FPGA-based 10-Gbit Ethernet Data Acquisition Interface for the Upgraded Electronics of the ATLAS Liquid Argon Calorimeters

    CERN Document Server

    Grohs, J P; The ATLAS collaboration

    2013-01-01

    The readout of the trigger signals of the ATLAS Liquid Argon (LAr) calorimeters is foreseen to be upgraded in order to prepare for operation during the first high-luminosity phase of the Large Hadron Collider (LHC). Signals with improved spatial granularity are planned to be received from the detector by a Digitial Processing System (DPS) in ATCA technology and will be sent in real-time to the ATLAS trigger system using custom optical links. These data are also sampled by the DPS for monitoring and will be read out by the regular Data Acquisition (DAQ) system of ATLAS which is a network-based PC-farm. The bandwidth between DPS module and DAQ system is expected to be in the order of 10 Gbit/s per module and a standard Ethernet protocol is foreseen to be used. DSP data will be prepared and sent by a modern FPGA either through a switch or directly to a Read-Out System (ROS) PC serving as buffer interface of the ATLAS DAQ. In a prototype setup, an ATCA blade equipped with a Xilinx Virtex-5 FPGA is used to send da...

  16. 28 May 2010 - Representatives of the Netherlands School of Public Administration guided in the ATLAS visitor centre by ATLAS Collaboration Member and NIKHEF G. Bobbink and ATLAS Magnet Project Leader H.ten Kate.

    CERN Document Server

    Maximilien Brice

    2010-01-01

    28 May 2010 - Representatives of the Netherlands School of Public Administration guided in the ATLAS visitor centre by ATLAS Collaboration Member and NIKHEF G. Bobbink and ATLAS Magnet Project Leader H.ten Kate.

  17. Analytics Platform for ATLAS Computing Services

    CERN Document Server

    Vukotic, Ilija; The ATLAS collaboration; Bryant, Lincoln

    2016-01-01

    Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Log file data and database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data so as to simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning tools like Spark, Jupyter, R, S...

  18. ATLAS Cloud Computing R&D project

    CERN Document Server

    Panitkin, S; The ATLAS collaboration; Caballero Bejar, J; Benjamin, D; DiGirolamo, A; Gable, I; Hendrix, V; Hover, J; Kucharczuk, K; Medrano LLamas, R; Ohman, H; Paterson, M; Sobie, R; Taylor, R; Walker, R; Zaytsev, A

    2013-01-01

    The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained...

  19. ATLAS: last few metresfor the Calorimeter

    CERN Multimedia

    2005-01-01

    On Friday 4th November, the ATLAS Barrel Calorimeter was moved from its assembly point at the side of the ATLAS cavern to the centre of the toroidal magnet system. The detector was finally aligned, to the precision of within a millimetre, on Wednesday 9th November. The ATLAS installation team, led by Tommi Nyman, after having positioned the Barrel Calorimeter in its final location in the ATLAS experimental cavern UX15. The Barrel Calorimeter which will absorb and measure the energy of photons, electrons and hadrons at the core of the ATLAS detector is 8.6 meters in diameter, 6.8 meters long, and weighs over 1600 Tonnes. It consists of two concentric cylindrical detector elements. The innermost comprises aluminium pressure vessels containing the liquid argon electromagnetic calorimeter and the solenoid magnet. The outermost is an assembly of 64 hadron tile calorimeter sectors. Assembled 18 meters away from its final position, the Barrel Calorimeter was relocated with the help of a railway, which allows the ...

  20. The ATLAS Level-1 Calorimeter Trigger

    International Nuclear Information System (INIS)

    Achenbach, R; Andrei, V; Adragna, P; Apostologlou, P; Barnett, B M; Brawn, I P; Davis, A O; Edwards, J P; Asman, B; Bohm, C; Ay, C; Bauss, B; Bendel, M; Dahlhoff, A; Eckweiler, S; Booth, J R A; Thomas, P Bright; Charlton, D G; Collins, N J; Curtis, C J

    2008-01-01

    The ATLAS Level-1 Calorimeter Trigger uses reduced-granularity information from all the ATLAS calorimeters to search for high transverse-energy electrons, photons, τ leptons and jets, as well as high missing and total transverse energy. The calorimeter trigger electronics has a fixed latency of about 1 μs, using programmable custom-built digital electronics. This paper describes the Calorimeter Trigger hardware, as installed in the ATLAS electronics cavern

  1. The ATLAS Level-1 Calorimeter Trigger

    Energy Technology Data Exchange (ETDEWEB)

    Achenbach, R; Andrei, V [Kirchhoff-Institut fuer Physik, University of Heidelberg, D-69120 Heidelberg (Germany); Adragna, P [Physics Department, Queen Mary, University of London, London E1 4NS (United Kingdom); Apostologlou, P; Barnett, B M; Brawn, I P; Davis, A O; Edwards, J P [STFC Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, Oxon OX11 0QX (United Kingdom); Asman, B; Bohm, C [Fysikum, Stockholm University, SE-106 91 Stockholm (Sweden); Ay, C; Bauss, B; Bendel, M; Dahlhoff, A; Eckweiler, S [Institut fuer Physik, University of Mainz, D-55099 Mainz (Germany); Booth, J R A; Thomas, P Bright; Charlton, D G; Collins, N J; Curtis, C J [School of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT (United Kingdom)], E-mail: e.eisenhandler@qmul.ac.uk (and others)

    2008-03-15

    The ATLAS Level-1 Calorimeter Trigger uses reduced-granularity information from all the ATLAS calorimeters to search for high transverse-energy electrons, photons, {tau} leptons and jets, as well as high missing and total transverse energy. The calorimeter trigger electronics has a fixed latency of about 1 {mu}s, using programmable custom-built digital electronics. This paper describes the Calorimeter Trigger hardware, as installed in the ATLAS electronics cavern.

  2. The future of PanDA in ATLAS distributed computing

    Science.gov (United States)

    De, K.; Klimentov, A.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Petrosyan, A.; Schovancova, J.; Vaniachine, A.; Wenaus, T.

    2015-12-01

    Experiments at the Large Hadron Collider (LHC) face unprecedented computing challenges. Heterogeneous resources are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, while data processing requires more than a few billion hours of computing usage per year. The PanDA (Production and Distributed Analysis) system was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. In the process, the old batch job paradigm of locally managed computing in HEP was discarded in favour of a far more automated, flexible and scalable model. The success of PanDA in ATLAS is leading to widespread adoption and testing by other experiments. PanDA is the first exascale workload management system in HEP, already operating at more than a million computing jobs per day, and processing over an exabyte of data in 2013. There are many new challenges that PanDA will face in the near future, in addition to new challenges of scale, heterogeneity and increasing user base. PanDA will need to handle rapidly changing computing infrastructure, will require factorization of code for easier deployment, will need to incorporate additional information sources including network metrics in decision making, be able to control network circuits, handle dynamically sized workload processing, provide improved visualization, and face many other challenges. In this talk we will focus on the new features, planned or recently implemented, that are relevant to the next decade of distributed computing workload management using PanDA.

  3. Atlas of Yellowstone

    Science.gov (United States)

    Pierce, Kenneth L.; Marcus, A. W.; Meachan, J. E.; Rodman, A. W.; Steingisser, A. Y.; Allan, Stuart; West, Ross

    2012-01-01

    Established in 1872, Yellowstone National Park was the world’s first national park. In a fitting tribute to this diverse and beautiful region, the Atlas of Yellowstone is a compelling visual guide to this unique national park and its surrounding area. Ranging from art to wolves, from American Indians to the Yellowstone Volcano, and from geysers to population, each page explains something new about the dynamic forces shaping Yellowstone. Equal parts reference and travel guide, the Atlas of Yellowstone is an unsurpassed resource.

  4. ATLAS Facility and Instrumentation Description Report

    International Nuclear Information System (INIS)

    Kang, Kyoung Ho; Moon, Sang Ki; Park, Hyun Sik

    2009-06-01

    A thermal-hydraulic integral effect test facility, ATLAS (Advanced Thermal-hydraulic Test Loop for Accident Simulation), has been constructed at KAERI (Korea Atomic Energy Research Institute). The ATLAS is a half-height and 1/288-volume scaled test facility with respect to the APR1400. The fluid system of the ATLAS consists of a primary system, a secondary system, a safety injection system, a break simulating system, a containment simulating system, and auxiliary systems. The primary system includes a reactor vessel, two hot legs, four cold legs, a pressurizer, four reactor coolant pumps, and two steam generators. The secondary system of the ATLAS is simplified to be of a circulating looptype. Most of the safety injection features of the APR1400 and the OPR1000 are incorporated into the safety injection system of the ATLAS. In the ATLAS test facility, about 1300 instrumentations are installed to precisely investigate the thermal-hydraulic behavior in simulation of the various test scenarios. This report describes the scaling methodology, the geometric data of the individual component, and the specification and the location of the instrumentations which are specific to the simulation of 50% DVI line break accident of the APR1400 for supporting the 50 th OECD/NEA International Standard Problem Exercise (ISP-50)

  5. Quark versus Gluon Jet Tagging Using Jet Images with the ATLAS Detector

    CERN Document Server

    The ATLAS collaboration

    2017-01-01

    Distinguishing quark-initiated from gluon-initiated jets is useful for many measurements and searches at the LHC. This note presents a jet tagger for distinguishing quark-initiated from gluon-initiated jets, which uses the full radiation pattern inside a jet processed as an image in a deep neural network classifier. The study is conducted using simulated dijet events in $\\sqrt{s}$=13 TeV pp collisions with the ATLAS detector. Across a wide range of quark jet identification efficiencies, the neural network tagger achieves a gluon jet rejection that is comparable to or better than the performance of the jet width and track multiplicity observables conventionally used for quark-versus-gluon jet tagging.

  6. Report to users of ATLAS, December 1995

    International Nuclear Information System (INIS)

    Ahmad, I.; Glagola, B.

    1995-12-01

    This report covers the following: status of ATLAS accelerator; highlights of recent research at ATLAS; research related concept for an Advanced Exotic Beam Facility on ATLAS; program advisory committee; and ATLAS user group executive committee. Research highlights are given for the following: APEX progress report; transport efficiency of the Argonne Fragment Mass Analyzer; collective motion in light polonium isotopes; angular correlation measurements for 12 C(g.s.) + 12 C(3-,9.64MeV) inelastic scattering; and the AYE-ball (Argonne-Yale-European gamma spectrometer) used to study the structure of nuclei far from stability

  7. The forward Detectors of the ATLAS experiment

    CERN Document Server

    Vittori, Camilla; The ATLAS collaboration

    2017-01-01

    In this poster, a review of the ATLAS forward detectors operating in the 2015-2016 data taking is given. This includes a description of LUCID, the preferred ATLAS luminosity provider; of the ALFA detector, aimed to measure elastically scattered protons at small angle for the total proton-proton cross section measurement; of the ATLAS Forward Proton project AFP, which was partially installed and took the first data in 2015, and of the Zero Degree Calorimeter ZDC built for the ATLAS Heavy Ions physics program. The near future plans for these detectors will also be addressed.

  8. FELIX: The new detector readout system for the ATLAS experiment

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00370160; The ATLAS collaboration

    2017-01-01

    After the Phase-I upgrades (2019) of the ATLAS experiment, the Front-End Link eXchange (FELIX) system will be the interface between the data acquisition system and the detector front-end and trigger electronics. FELIX will function as a router between custom serial links and a commodity switch network using standard technologies (Ethernet or Infiniband) to communicate with commercial data collecting and processing components. The system architecture of FELIX will be described and the status of the firmware implementation and hardware development currently in progress will be presented.

  9. FELIX: The new detector readout system for the ATLAS experiment

    Science.gov (United States)

    Ryu, Soo; ATLAS TDAQ Collaboration

    2017-10-01

    After the Phase-I upgrades (2019) of the ATLAS experiment, the Front-End Link eXchange (FELIX) system will be the interface between the data acquisition system and the detector front-end and trigger electronics. FELIX will function as a router between custom serial links and a commodity switch network using standard technologies (Ethernet or Infiniband) to communicate with commercial data collecting and processing components. The system architecture of FELIX will be described and the status of the firmware implementation and hardware development currently in progress will be presented.

  10. Trigger Menu-aware Monitoring for the ATLAS experiment

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00441925; The ATLAS collaboration

    2017-01-01

    Changes in the trigger menu, the online algorithmic event-selection of the ATLAS experiment at the LHC, are followed by adjustments to the ATLAS trigger monitoring systems. During Run 1, and so far in Run 2, ATLAS has deployed monitoring updates with the installation of new software releases at Tier-0, the first level of the ATLAS computing grid. Having to wait for a new software release to be installed at Tier-0, in order to update ATLAS offline trigger monitoring configurations, results in a lag with respect to the modification of the trigger menu. We present the design and implementation of a `trigger menu-aware' monitoring system that aims to simplify the ATLAS operational workflows by allowing monitoring configuration changes to be made at the Tier-0 site by utilising an Oracle SQL database.

  11. ATLAS production system

    CERN Document Server

    Borodin, Mikhail; The ATLAS collaboration; De, Kaushik; Klimentov, Alexei; Golubkov, Dmitry; Maeno, Tadashi; Mashinistov, Ruslan; Wenaus, Torre; Padolski, Siarhei

    2016-01-01

    The second generation of the ATLAS production system called ProdSys2 is a distributed workload manager which used by thousands of physicists to analyze the data remotely, with the volume of processed data is beyond the exabyte scale, across a more than hundred heterogeneous sites. It achieves high utilization by combining dynamic job definition based on many criterias, such as input and output size, memory requirements and CPU consumption with manageable scheduling policies and by supporting different kind of computational resources, such as GRID, clouds, supercomputers and volunteering computers. Besides jobs definition Production System also includes flexible web user interface, which implements user-friendly environment for main ATLAS workflows, e.g. simple way of combining different data flows, and real-time monitoring, optimised for using with huge amount of information to present. We present an overview of the ATLAS Production System major components: job and task definition, workflow manager web user i...

  12. ATLAS rewards industry

    CERN Multimedia

    2006-01-01

    Showing excellence in mechanics, electronics and cryogenics, three industries are honoured for their contributions to the ATLAS experiment. Representatives of the three award-wining companies after the ceremony. For contributing vital pieces to the ATLAS puzzle, three industries were recognized on Friday 5 May during a supplier awards ceremony. After a welcome and overview of the ATLAS experiment by spokesperson Peter Jenni, CERN Secretary-General Maximilian Metzger stressed the importance of industry to CERN's scientific goals. Close interaction with CERN was a key factor in the selection of each rewarded company, in addition to the high-quality products they delivered to the experiment. Alu Menziken Industrie AG, of Switzerland, was honoured for the production of 380,000 aluminium tubes for the Monitored Drift Tube Chambers (MDT). As Giora Mikenberg, the Muon System Project Leader stressed, the aluminium tubes were delivered on time with an extraordinary quality and precision. Between October 2000 and Jan...

  13. The evolving role of Tier2s in ATLAS with the new Computing and Data Distribution model

    International Nuclear Information System (INIS)

    González de la Hoz, S

    2012-01-01

    Originally the ATLAS Computing and Data Distribution model assumed that the Tier-2s should keep on disk collectively at least one copy of all “active” AOD and DPD datasets. Evolution of ATLAS Computing and Data model requires changes in ATLAS Tier-2s policy for the data replication, dynamic data caching and remote data access. Tier-2 operations take place completely asynchronously with respect to data taking. Tier-2s do simulation and user analysis. Large-scale reprocessing jobs on real data are at first taking place mostly at Tier-1s but will progressively be shared with Tier-2s as well. The availability of disk space at Tier-2s is extremely important in the ATLAS Computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier-2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier-2s are going to be used more efficiently. In this way Tier-1s and Tier-2s are becoming more equivalent for the network and the hierarchy of Tier-1, 2 is less strict. This paper presents the usage of Tier-2s resources in different Grid activities, caching of data at Tier-2s, and their role in the analysis in the new ATLAS Computing and Data model.

  14. Das Ausmalbuch zum ATLAS-Experiment

    CERN Multimedia

    Anthony, Katarina

    2017-01-01

    Deutsche Fassung - The ATLAS Experiment Colouring Book is a free-to-download educational book, ideal for kids aged 5-9. It aims to introduce children to the field of High-Energy Physics, as well as the work being carried out by the ATLAS Collaboration.

  15. Automated Loads Analysis System (ATLAS)

    Science.gov (United States)

    Gardner, Stephen; Frere, Scot; O’Reilly, Patrick

    2013-01-01

    ATLAS is a generalized solution that can be used for launch vehicles. ATLAS is used to produce modal transient analysis and quasi-static analysis results (i.e., accelerations, displacements, and forces) for the payload math models on a specific Shuttle Transport System (STS) flight using the shuttle math model and associated forcing functions. This innovation solves the problem of coupling of payload math models into a shuttle math model. It performs a transient loads analysis simulating liftoff, landing, and all flight events between liftoff and landing. ATLAS utilizes efficient and numerically stable algorithms available in MSC/NASTRAN.

  16. The ATLAS Distributed Data Management project: Past and Future

    CERN Document Server

    Garonne, V; The ATLAS collaboration; Lassnig, M; Molfetas, A; Barisits, M; Beermann, T; Nairz, A; Goossens, L; Barreiro Megino, F; Serfon, C; Oleynik, D; Petrosyan, A

    2012-01-01

    ATLAS has recorded almost 8PB of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 90PB is currently stored in the Worldwide LHC Computing Grid by ATLAS. All this data is managed by the ATLAS Distributed Data Management system, called Don Quijote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs, and to help ATLAS physicists get access to this data. In this paper, we describe new and improved DQ2 services, and the experience of data management operation in ATLAS computing, showing how these services enable the management of petabyte scale computing operations. We also present the concepts of the new version of the ATLAS Distributed Data Management (DDM) system, Rucio.

  17. The ATLAS Distributed Data Management project: Past and Future

    International Nuclear Information System (INIS)

    Garonne, Vincent; Stewart, Graeme A; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Beermann, Thomas; Nairz, Armin; Goossens, Luc; Barreiro Megino, Fernando; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem

    2012-01-01

    ATLAS has recorded more than 8 petabyte(PB) of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 90PB are currently stored in the Worldwide LHC Computing Grid by ATLAS. All these data are managed by the ATLAS Distributed Data Management system, called Don Quijote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs, and to help ATLAS physicists get access to these data. In this paper, we describe new and improved DQ2 services, and the experience of data management operation in ATLAS computing, showing how these services enable the management of PB scale computing operations. We also present the concepts of the new version of the ATLAS Distributed Data Management (DDM) system, Rucio.

  18. The ATLAS Distributed Data Management project: Past and Future

    Science.gov (United States)

    Garonne, Vincent; Stewart, Graeme A.; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Beermann, Thomas; Nairz, Armin; Goossens, Luc; Barreiro Megino, Fernando; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem

    2012-12-01

    ATLAS has recorded more than 8 petabyte(PB) of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 90PB are currently stored in the Worldwide LHC Computing Grid by ATLAS. All these data are managed by the ATLAS Distributed Data Management system, called Don Quijote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs, and to help ATLAS physicists get access to these data. In this paper, we describe new and improved DQ2 services, and the experience of data management operation in ATLAS computing, showing how these services enable the management of PB scale computing operations. We also present the concepts of the new version of the ATLAS Distributed Data Management (DDM) system, Rucio.

  19. Cassini Tour Atlas Automated Generation

    Science.gov (United States)

    Grazier, Kevin R.; Roumeliotis, Chris; Lange, Robert D.

    2011-01-01

    During the Cassini spacecraft s cruise phase and nominal mission, the Cassini Science Planning Team developed and maintained an online database of geometric and timing information called the Cassini Tour Atlas. The Tour Atlas consisted of several hundreds of megabytes of EVENTS mission planning software outputs, tables, plots, and images used by mission scientists for observation planning. Each time the nominal mission trajectory was altered or tweaked, a new Tour Atlas had to be regenerated manually. In the early phases of Cassini s Equinox Mission planning, an a priori estimate suggested that mission tour designers would develop approximately 30 candidate tours within a short period of time. So that Cassini scientists could properly analyze the science opportunities in each candidate tour quickly and thoroughly so that the optimal series of orbits for science return could be selected, a separate Tour Atlas was required for each trajectory. The task of manually generating the number of trajectory analyses in the allotted time would have been impossible, so the entire task was automated using code written in five different programming languages. This software automates the generation of the Cassini Tour Atlas database. It performs with one UNIX command what previously took a day or two of human labor.

  20. Dedication of the massive ATLAS art mural painted by Josef Kristofoletti directly above the cavern of the ATLAS Experiment at CERN

    CERN Multimedia

    Claudia Marcelloni, Michael Barnett

    2010-01-01

    Ceremony to celebrate the massive mural of the ATLAS detector at CERN painted by artist Josef Kristofoletti. The mural is located at the ATLAS Experiment site, and it shows on two perpendicular walls the detector with a collision event superimposed. The event on the large wall shows a simulation of an event that would be recorded in ATLAS if a Higgs boson was produced. The cavern of the ATLAS Experiment with the detector is 100 meters directly below the mural. The height of the mural is about 12 meters (40 feet). The actual ATLAS detector is more than twice as big.

  1. ProstAtlas: A digital morphologic atlas of the prostate

    International Nuclear Information System (INIS)

    Betrouni, N.; Iancu, A.; Puech, P.; Mordon, S.; Makni, N.

    2012-01-01

    Computer-aided medical interventions and medical robotics for prostate cancer have known an increasing interest and research activity. However before the routine deployment of these procedures in clinical practice becomes a reality, in vivo and in silico validations must be undertaken. In this study, we developed a digital morphologic atlas of the prostate. We were interested by the gland, the peripheral zone and the central gland. Starting from an image base collected from 30 selected patients, a mean shape and most important deformations for each structure were deduced using principal component analysis. The usefulness of this atlas was highlighted in two applications: image simulation and physical phantom design

  2. ATLAS Distributed Computing: Its Central Services core

    CERN Document Server

    Lee, Christopher Jon; The ATLAS collaboration

    2018-01-01

    The ATLAS Distributed Computing (ADC) Project is responsible for the off-line processing of data produced by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. It facilitates data and workload management for ATLAS computing on the Worldwide LHC Computing Grid (WLCG). ADC Central Services operations (CSops)is a vital part of ADC, responsible for the deployment and configuration of services needed by ATLAS computing and operation of those services on CERN IT infrastructure, providing knowledge of CERN IT services to ATLAS service managers and developers, and supporting them in case of issues. Currently this entails the management of thirty seven different OpenStack projects, with more than five thousand cores allocated for these virtual machines, as well as overseeing the distribution of twenty nine petabytes of storage space in EOS for ATLAS. As the LHC begins to get ready for the next long shut-down, which will bring in many new upgrades to allow for more data to be captured by the on-line syste...

  3. Argonne Tandem Linac Accelerator System (ATLAS)

    Data.gov (United States)

    Federal Laboratory Consortium — ATLAS is a national user facility at Argonne National Laboratory in Argonne, Illinois. The ATLAS facility is a leading facility for nuclear structure research in the...

  4. Bone age assessment in Hispanic children: digital hand atlas compared with the Greulich and Pyle (G&P) atlas

    Science.gov (United States)

    Fernandez, James Reza; Zhang, Aifeng; Vachon, Linda; Tsao, Sinchai

    2008-03-01

    Bone age assessment is most commonly performed with the use of the Greulich and Pyle (G&P) book atlas, which was developed in the 1950s. The population of theUnited States is not as homogenous as the Caucasian population in the Greulich and Pyle in the 1950s, especially in the Los Angeles, California area. A digital hand atlas (DHA) based on 1,390 hand images of children of different racial backgrounds (Caucasian, African American, Hispanic, and Asian) aged 0-18 years was collected from Children's Hospital Los Angeles. Statistical analysis discovered significant discrepancies exist between Hispanic and the G&P atlas standard. To validate the usage of DHA as a clinical standard, diagnostic radiologists performed reads on Hispanic pediatric hand and wrist computed radiography images using either the G&P pediatric radiographic atlas or the Children's Hospital Los Angeles Digital Hand Atlas (DHA) as reference. The order in which the atlas is used (G&P followed by DHA or vice versa) for each image was prepared before actual reading begins. Statistical analysis of the results was then performed to determine if a discrepancy exists between the two readings.

  5. Advances in service and operations for ATLAS data management

    International Nuclear Information System (INIS)

    Stewart, Graeme A; Garonne, Vincent; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Calvet, Ivan; Beermann, Thomas; Megino, Fernando Barreiro; Campana, Simone; Zhang, Donal; Tykhonov, Andrii; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem

    2012-01-01

    ATLAS has recorded almost 5PB of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 70PB is currently stored in the Worldwide LHC Computing Grid by ATLAS. All of this data is managed by the ATLAS Distributed Data Management system, called Don Quixote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs and to help ATLAS physicists get access to this data. In this paper we describe new and improved DQ2 services: popularity; space monitoring and accounting; exclusion service; cleaning agents; deletion agents. We describe the experience of data management operation in ATLAS computing, showing how these services enable management of petabyte scale computing operations. We illustrate the coupling of data management services to other parts of the ATLAS computing infrastructure, in particular showing how feedback from the distributed analysis system in ATLAS has enabled dynamic placement of the most popular data, helping users and groups to analyse the increasing data volumes on the grid.

  6. Advances in service and operations for ATLAS data management

    Science.gov (United States)

    Stewart, Graeme A.; Garonne, Vincent; Lassnig, Mario; Molfetas, Angelos; Barisits, Martin; Zhang, Donal; Calvet, Ivan; Beermann, Thomas; Barreiro Megino, Fernando; Tykhonov, Andrii; Campana, Simone; Serfon, Cedric; Oleynik, Danila; Petrosyan, Artem; ATLAS Collaboration

    2012-06-01

    ATLAS has recorded almost 5PB of RAW data since the LHC started running at the end of 2009. Many more derived data products and complimentary simulation data have also been produced by the collaboration and, in total, 70PB is currently stored in the Worldwide LHC Computing Grid by ATLAS. All of this data is managed by the ATLAS Distributed Data Management system, called Don Quixote 2 (DQ2). DQ2 has evolved rapidly to help ATLAS Computing operations manage these large quantities of data across the many grid sites at which ATLAS runs and to help ATLAS physicists get access to this data. In this paper we describe new and improved DQ2 services: popularity; space monitoring and accounting; exclusion service; cleaning agents; deletion agents. We describe the experience of data management operation in ATLAS computing, showing how these services enable management of petabyte scale computing operations. We illustrate the coupling of data management services to other parts of the ATLAS computing infrastructure, in particular showing how feedback from the distributed analysis system in ATLAS has enabled dynamic placement of the most popular data, helping users and groups to analyse the increasing data volumes on the grid.

  7. Budker INP in ATLAS

    CERN Multimedia

    2001-01-01

    The Novosibirsk group has proposed a new design for the ATLAS liquid argon electromagnetic end-cap calorimeter with a constant thickness of absorber plates. This design has signifi- cant advantages compared to one in the Technical Proposal and it has been accepted by the ATLAS Collaboration. The Novosibirsk group is responsible for the fabrication of the precision aluminium structure for the e.m.end-cap calorimeter.

  8. Custom-made power for ATLAS

    CERN Multimedia

    2005-01-01

    A small team of engineers and technicians has recently finished the design of power supplies specially tailored to working in the demanding environment of the ATLAS Tile Calorimeter. Mass production of the units has now begun. The ATLAS Tile Calorimeter power supply development team (left to right): Ivan Hruska (holding brick), Francisca Calheiros, Bohuslav Palan, Jiri Palacky and Zdenek Kotek. Power supplies are an important component of any particle detector. In ATLAS, as in the other experiments at the Large Hadron Collider, it is not easy to use standard, 'off the shelf' power supplies; they must survive radiation, tolerate magnetic fields, and satisfy limited space and water-cooling constraints. For the ATLAS Tile Calorimeter, these constraints all proved challenging for the engineers designing the power supplies. The aim was to produce a universal power module in terms of input/output voltage, delivered power and cooling, for general use in a radiation environment. The result is a distributed low-vo...

  9. Two new wheels for ATLAS

    CERN Multimedia

    2002-01-01

    Juergen Zimmer (Max Planck Institute), Roy Langstaff (TRIUMF/Victoria) and Sergej Kakurin (JINR), in front of one of the completed wheels of the ATLAS Hadronic End Cap Calorimeter. A decade of careful preparation and construction by groups in three continents is nearing completion with the assembly of two of the four 4 m diameter wheels required for the ATLAS Hadronic End Cap Calorimeter. The first two wheels have successfully passed all their mechanical and electrical tests, and have been rotated on schedule into the vertical position required in the experiment. 'This is an important milestone in the completion of the ATLAS End Cap Calorimetry' explains Chris Oram, who heads the Hadronic End Cap Calorimeter group. Like most experiments at particle colliders, ATLAS consists of several layers of detectors in the form of a 'barrel' and two 'end caps'. The Hadronic Calorimeter layer, which measures the energies of particles such as protons and pions, uses two techniques. The barrel part (Tile Calorimeter) cons...

  10. The ATLAS Distributed Analysis System

    CERN Document Server

    Legger, F; The ATLAS collaboration; Pacheco Pages, A; Stradling, A

    2013-01-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During the first run of the LHC, the ATLAS Distributed Analysis (DA) service has operated stably and scaled as planned. More than 1600 users submitted jobs in 2012, with 2 million or more analysis jobs per week, peaking at about a million jobs per day. The system dynamically distributes popular data to expedite processing and maximally utilize resources. The reliability of the DA service is high but steadily improving; grid sites are continually validated against a set of standard tests, and a dedicated team of expert shifters ...

  11. The ATLAS Distributed Analysis System

    CERN Document Server

    Legger, F; The ATLAS collaboration

    2014-01-01

    In the LHC operations era, analysis of the multi-petabyte ATLAS data sample by globally distributed physicists is a challenging task. To attain the required scale the ATLAS Computing Model was designed around the concept of grid computing, realized in the Worldwide LHC Computing Grid (WLCG), the largest distributed computational resource existing in the sciences. The ATLAS experiment currently stores over 140 PB of data and runs about 140,000 concurrent jobs continuously at WLCG sites. During the first run of the LHC, the ATLAS Distributed Analysis (DA) service has operated stably and scaled as planned. More than 1600 users submitted jobs in 2012, with 2 million or more analysis jobs per week, peaking at about a million jobs per day. The system dynamically distributes popular data to expedite processing and maximally utilize resources. The reliability of the DA service is high but steadily improving; grid sites are continually validated against a set of standard tests, and a dedicated team of expert shifters ...

  12. ATLAS: Now under new management

    CERN Multimedia

    Katarina Anthony

    2013-01-01

    On 1 March, the ATLAS Collaboration welcomed a new spokesperson, Dave Charlton (University of Birmingham), and two new deputy spokespersons, Thorsten Wengler (CERN) and Beate Heinemann (University of California, Berkeley and LBNL). The Bulletin takes a look at what’s in store for one of the world’s largest scientific collaborations.   ATLAS members at the 2010 collaboration meeting in Copenhagen. Image: Rune Johansen and Troels Petersen. ATLAS spokesperson Dave Charlton has seen the collaboration through countless milestones: from construction to start-up to the 4 July 2012 announcement, he’s been an integral part of the team. Now, after twelve years with the collaboration, Dave is moving into the main office for the next two years. “2012 was a landmark year for ATLAS,” says Dave. “We spent a lot of time in the limelight and, in many ways, all eyes are still on us. But with the shutdown now under way, our focus is ...

  13. ATLAS recognises its best suppliers

    CERN Multimedia

    Jenni, P

    The ATLAS Collaboration has recently rewarded two of its suppliers in the construction of very major detector components, fabricated in Japan. The ATLAS Supplier Award in recognition of excellent supplier performance was attributed on 2nd September 2002 during a ceremony in Hall 180 to Kawasaki Heavy Industries, while Toshiba Corporation received the award two months before at their headquarters in Japan. The ATLAS experiment will become a reality thanks to a large international collaboration partnership. The industrial suppliers for the components all over the world play a major role in the construction of this gigantic jigsaw for the LHC. And sometimes they perform so well, that their work deserves specially to be recognised. This is the case for Kawasaki Heavy Industries and Toshiba Corporation, producers of the Liquid Argon Barrel Cryostat and of the Superconducting Central Solenoid, respectively. With these awards, the ATLAS Collaboration wants to congratulate Kawasaki and Toshiba for fulfilling the hi...

  14. ATLAS Software Installation on Supercomputers

    CERN Document Server

    Undrus, Alexander; The ATLAS collaboration

    2018-01-01

    PowerPC and high performance computers (HPC) are important resources for computing in the ATLAS experiment. The future LHC data processing will require more resources than Grid computing, currently using approximately 100,000 cores at well over 100 sites, can provide. Supercomputers are extremely powerful as they use resources of hundreds of thousands CPUs joined together. However their architectures have different instruction sets. ATLAS binary software distributions for x86 chipsets do not fit these architectures, as emulation of these chipsets results in huge performance loss. This presentation describes the methodology of ATLAS software installation from source code on supercomputers. The installation procedure includes downloading the ATLAS code base as well as the source of about 50 external packages, such as ROOT and Geant4, followed by compilation, and rigorous unit and integration testing. The presentation reports the application of this procedure at Titan HPC and Summit PowerPC at Oak Ridge Computin...

  15. Non-collision backgrounds in ATLAS

    CERN Document Server

    Gibson, S M; The ATLAS collaboration

    2012-01-01

    The proton-proton collision events recorded by the ATLAS experiment are on top of a background that is due to both collision debris and non-collision components. The latter comprises of three types: beam-induced backgrounds, cosmic particles and detector noise. We present studies that focus on the first two of these. We give a detailed description of beam-related and cosmic backgrounds based on the full 2011 ATLAS data set, and present their rates throughout the whole data-taking period. Studies of correlations between tertiary proton halo and muon backgrounds, as well as, residual pressure and resulting beam-gas events seen in beam-condition monitors will be presented. Results of simulations based on the LHC geometry and its parameters will be presented. They help to better understand the features of beam-induced backgrounds in each ATLAS sub-detector. The studies of beam-induced backgrounds in ATLAS reveal their characteristics and serve as a basis for designing rejection tools that can be applied in physic...

  16. Fabiola Gianotti, the newly elected Spokesperson of ATLAS

    CERN Multimedia

    2008-01-01

    On 11 July Fabiola Gianotti was elected by the ATLAS Collaboration as its future Spokesperson. Her term of office will start on 1 March 2009 and will last for two years. She will take over from Peter Jenni who has been ATLAS Spokesperson since its formalization in 1992. Three distinguished physicists stood as candidates for this election: Fabiola Gianotti (CERN), Marzio Nessi (CERN), and Leonardo Rossi (INFN Genova, Italy). The nomination process started on 30 October 2007, with a general email sent to the ATLAS collaboration calling for nominations, and closed on 25 January 2008. Any ATLAS physicist could nominate a candidate, and 24 nominees were proposed before the ATLAS search committee narrowed them to the final three. After the voting process, which concluded the ATLAS general meeting in Bern, the Collaboration Board greeted the result with warm applause.

  17. Special people visit the ATLAS cavern

    CERN Multimedia

    Muriel

    ATLAS has been host to many important visitors lately. Here are a selected few: Professor Stephen Hawking visits the ATLAS cavern On Tuesday 26 September 2006 the ATLAS Collaboration was honoured by a very special visit to the detector in the underground cavern. We were pleased to guide Professor Stephen Hawking, the famous cosmologist holding the post of Lucasian Professor of Mathematics at Cambridge University (position held by Isaac Newton in the 17th century), on a tour of the ATLAS pit and the LHC tunnel. The visit was accompanied by a few colleagues from the CERN Theory group, and was only possible thanks to the professional assistance of Olga Beltramello and Bernard Lebegue, who had also taken care of all the necessary preparatory work in the cavern. Professor Hawking was very keen to check for himself the status of the detector installation, and he admired, in particular, the spectacular TGC big wheel on side C. (left) Stephen Hawking in the ATLAS cavern side-C (right) and in the LHC tunnel...

  18. Machine Learning Algorithms for $b$-Jet Tagging at the ATLAS Experiment

    CERN Document Server

    Paganini, Michela; The ATLAS collaboration

    2017-01-01

    The separation of b-quark initiated jets from those coming from lighter quark flavours (b-tagging) is a fundamental tool for the ATLAS physics program at the CERN Large Hadron Collider. The most powerful b-tagging algorithms combine information from low-level taggers exploiting reconstructed track and vertex information using a multivariate classifier. The potential of modern Machine Learning techniques such as Recurrent Neural Networks and Deep Learning is explored using simulated events, and compared to that achievable from more traditional classifiers such as boosted decision trees.

  19. The Pig PeptideAtlas

    DEFF Research Database (Denmark)

    Hesselager, Marianne Overgaard; Codrea, Marius; Sun, Zhi

    2016-01-01

    Biological research of Sus scrofa, the domestic pig, is of immediate relevance for food production sciences, and for developing pig as a model organism for human biomedical research. Publicly available data repositories play a fundamental role for all biological sciences, and protein data...... repositories are in particular essential for the successful development of new proteomic methods. Cumulative proteome data repositories, including the PeptideAtlas, provide the means for targeted proteomics, system-wide observations, and cross-species observational studies, but pigs have so far been...... underrepresented in existing repositories. We here present a significantly improved build of the Pig PeptideAtlas, which includes pig proteome data from 25 tissues and three body fluid types mapped to 7139 canonical proteins. The content of the Pig PeptideAtlas reflects actively ongoing research within...

  20. Search for single top-quark production via flavour-changing neutral currents at 8 TeV with the ATLAS detector

    Czech Academy of Sciences Publication Activity Database

    Aad, G.; Abbott, B.; Abdallah, J.; Chudoba, Jiří; Havránek, Miroslav; Hejbal, Jiří; Jakoubek, Tomáš; Kepka, Oldřich; Kupčo, Alexander; Kůs, Vlastimil; Lokajíček, Miloš; Lysák, Roman; Marčišovský, Michal; Mikeštíková, Marcela; Němeček, Stanislav; Penc, Ondřej; Šícho, Petr; Staroba, Pavel; Svatoš, Michal; Taševský, Marek; Vrba, Václav

    2016-01-01

    Roč. 76, č. 2 (2016), s. 1-29, č. článku 55. ISSN 1434-6044 Institutional support: RVO:68378271 Keywords : ATLAS * neural network * CERN LHC Coll * initial state * new physics Subject RIV: BF - Elementary Particles and High Energy Physics Impact factor: 5.331, year: 2016

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