Application of a 3-D Super Ensemble to ocean forecast
Lenartz, F.; Barth, A.; Beckers, J.-M.; Vandenbulcke, L.; Rixen, M.
2009-04-01
Super Ensemble (SE) techniques have recently allowed improving the forecast of various important oceanographic parameters, such as the significant wave height, the speed of sound or the surface drift, by correcting the prediction at a single or multiple locations, where data were available during the whole training period. However, nowadays common observation systems, such as satellite imagery or drifters, do not always provide information at the exact same locations, hence it is necessary to generalize the approach in order to take benefit of every image or track available. In this study, we try and apply a SE, fed with remote sensing and gliders data, to 3-D hydrodynamic models. The basic idea on which rely the SE methods is that a certain combination of several model runs and possibly data could yield better results than just one single model, even if it has a higher temporal or spatial resolution. As the most efficient techniques are the ones using observations, they rapidly developed and increased in complexity by copying what had been done in the data assimilation community; getting from the simple ensemble mean of the model outputs to their linear combination based on a particle filter. In our present study, we have decided to use the Kalman filter (KF) as it alleviates the need of an a priori determination of the training period length, and does not require the run of a very large ensemble of members. In addition, we apply it in a 3-D framework in order to take benefit of the spatial information contained by each source of measurements. For example, satellite images of sea surface temperature (SST) are very useful to correct the value of this parameter, but depending on the structure of the water column, it can also give a precious guess of how warm or cold is the ocean at 20 m deep. In our experiment the domain of interest is the Ligurian Sea during the last week of September, when part of the set-up for the CalVal08 campaign (SiC Charles Trees) had
Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case
Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann
2017-04-01
Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.
Multimodel SuperEnsemble technique for quantitative precipitation forecasts in Piemonte region
Directory of Open Access Journals (Sweden)
D. Cane
2010-02-01
Full Text Available The Multimodel SuperEnsemble technique is a powerful post-processing method for the estimation of weather forecast parameters reducing direct model output errors. It has been applied to real time NWP, TRMM-SSM/I based multi-analysis, Seasonal Climate Forecasts and Hurricane Forecasts. The novelty of this approach lies in the methodology, which differs from ensemble analysis techniques used elsewhere.
Several model outputs are put together with adequate weights to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure, the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts, involving a new accurate statistical method for bias correction and a wide spectrum of results over Piemonte very dense non-GTS weather station network.
Regional climate models downscaling in the Alpine area with Multimodel SuperEnsemble
Directory of Open Access Journals (Sweden)
D. Cane
2012-08-01
Full Text Available The climatic scenarios show a strong signal of warming in the Alpine area already for the mid XXI century. The climate simulations, however, even when obtained with Regional Climate Models (RCMs, are affected by strong errors where compared with observations, due to their difficulties in representing the complex orography of the Alps and limitations in their physical parametrization.
Therefore the aim of this work is reducing these model biases using a specific post processing statistic technique to obtain a more suitable projection of climate change scenarios in the Alpine area.
For our purposes we use a selection of RCMs runs from the ENSEMBLES project, carefully chosen in order to maximise the variety of leading Global Climate Models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observation for the Greater Alpine Area are extracted from the European dataset E-OBS produced by the project ENSEMBLES with an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (1957–present were carefully gridded on a 14-km grid over Piedmont Region with an Optimal Interpolation technique.
Hence, we applied the Multimodel SuperEnsemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period.
We propose also the first application to RCMS of a brand new probabilistic Multimodel SuperEnsemble Dressing technique to estimate precipitation fields, already applied successfully to weather forecast models, with careful description of precipitation Probability Density Functions conditioned to the model outputs. This technique reduces the strong precipitation overestimation by RCMs over the alpine chain and reproduces well the monthly behaviour of precipitation in the control period.
Hoze, N; Holcman, D
2015-11-01
Recovering a stochastic process from noisy ensembles of single-particle trajectories is resolved here using the coarse-grained Langevin equation as a model. The massive redundancy contained in single-particle tracking data allows recovering local parameters of the underlying physical model. We use several parametric and nonparametric estimators to compute the first and second moments of the process, to recover the local drift, its derivative, and the diffusion tensor, and to deconvolve the instrumental from the physical noise. We use numerical simulations to also explore the range of validity for these estimators. The present analysis allows defining what can exactly be recovered from statistics of super-resolution microscopy trajectories used for characterizing molecular trafficking underlying cellular functions.
Optical far-field super-resolution microscopy using nitrogen vacancy center ensemble in bulk diamond
Li, Shen; Chen, Xiang-dong; Zhao, Bo-Wen; Dong, Yang; Zou, Chong-Wen; Guo, Guang-Can; Sun, Fang-Wen
2016-09-01
We demonstrate optical far-field super-resolution microscopy using an array of nitrogen vacancy centers in bulk diamond as near-field optical probes. The local optical field, which transmits through the nanostructures on the diamond surface, is measured by detecting the charge state conversion of the nitrogen vacancy center. Locating the nitrogen vacancy center with a spatial resolution of 6.1 nm is realized with charge state depletion nanoscopy. The nanostructures on the surface of a diamond are then imaged with a resolution below the optical diffraction limit. The results offer an approach to build a general-purpose optical super-resolution microscopy technique and a convenient platform for high spatial resolution quantum sensing with nitrogen vacancy centers.
Optical far-field super-resolution microscopy using nitrogen vacancy center ensemble in bulk diamond
Li, Shen; Zhao, Bo-Wen; Dong, Yang; Zou, Chong-Wen; Guo, Guang-Can; Sun, Fang-Wen
2016-01-01
We demonstrate an optical far-field super-resolution microscopy using array of nitrogen vacancy centers in bulk diamond as near-field optical probes. The local optical field, which transmits through the nanostructures on the diamond surface, is measured by detecting the charge state conversion of nitrogen vacancy center. And the locating of nitrogen vacancy center with spatial resolution of 6.1 nm is realized with the charge state depletion nanoscopy. The nanostructures on the surface of diamond are then imaged with resolution below optical diffraction limit. The results offer an approach to built a general-purpose optical super-resolution microscopy and a convenient platform for high spatial resolution quantum sensing with nitrogen vacancy center.
Optical far-field super-resolution microscopy using nitrogen vacancy center ensemble in bulk diamond
Li, Shen; Chen, Xiang-Dong; Zhao, Bo-Wen; Dong, Yang; Zou, Chong-Wen; Guo, Guang-Can; Sun, Fang-Wen
2016-01-01
We demonstrate an optical far-field super-resolution microscopy using array of nitrogen vacancy centers in bulk diamond as near-field optical probes. The local optical field, which transmits through the nanostructures on the diamond surface, is measured by detecting the charge state conversion of nitrogen vacancy center. And the locating of nitrogen vacancy center with spatial resolution of 6.1 nm is realized with the charge state depletion nanoscopy. The nanostructures on the surface of diam...
Directory of Open Access Journals (Sweden)
Baptiste Mourre
2014-01-01
Full Text Available This study compares the ability of two approaches integrating models and data to forecast the Ligurian Sea regional oceanographic conditions in the short-term range (0–72 hours when constrained by a common observation dataset. The post-processing 3-D super-ensemble (3DSE algorithm, which uses observations to optimally combine multi-model forecasts into a single prediction of the oceanic variable, is first considered. The 3DSE predictive skills are compared to those of the Regional Ocean Modeling System model in which observations are assimilated through a more conventional ensemble Kalman filter (EnKF approach. Assimilated measurements include sea surface temperature maps, and temperature and salinity subsurface observations from a fleet of five underwater gliders. Retrospective analyses are carried out to produce daily predictions during the 11-d period of the REP10 sea trial experiment. The forecast skill evaluation based on a distributed multi-sensor validation dataset indicates an overall superior performance of the EnKF, both at the surface and at depth. While the 3DSE and EnKF perform comparably well in the area spanned by the incorporated measurements, the 3DSE accuracy is found to rapidly decrease outside this area. In particular, the univariate formulation of the method combined with the absence of regular surface salinity measurements produces large errors in the 3DSE salinity forecast. On the contrary, the EnKF leads to more homogeneous forecast errors over the modelling domain for both temperature and salinity. The EnKF is found to consistently improve the predictions with respect to the control solution without assimilation and to be positively skilled when compared to the climatological estimate. For typical regional oceanographic applications with scarce subsurface observations, the lack of physical spatial and multivariate error covariances applicable to the individual model weights in the 3DSE formulation constitutes a major
Brochero, Darwin; Hajji, Islem; Pina, Jasson; Plana, Queralt; Sylvain, Jean-Daniel; Vergeynst, Jenna; Anctil, Francois
2015-04-01
Theories about generalization error with ensembles are mainly based on the diversity concept, which promotes resorting to many members of different properties to support mutually agreeable decisions. Kuncheva (2004) proposed the Multi Level Diversity Model (MLDM) to promote diversity in model ensembles, combining different data subsets, input subsets, models, parameters, and including a combiner level in order to optimize the final ensemble. This work tests the hypothesis about the minimisation of the generalization error with ensembles of Neural Network (NN) structures. We used the MLDM to evaluate two different scenarios: (i) ensembles from a same NN architecture, and (ii) a super-ensemble built by a combination of sub-ensembles of many NN architectures. The time series used correspond to the 12 basins of the MOdel Parameter Estimation eXperiment (MOPEX) project that were used by Duan et al. (2006) and Vos (2013) as benchmark. Six architectures are evaluated: FeedForward NN (FFNN) trained with the Levenberg Marquardt algorithm (Hagan et al., 1996), FFNN trained with SCE (Duan et al., 1993), Recurrent NN trained with a complex method (Weins et al., 2008), Dynamic NARX NN (Leontaritis and Billings, 1985), Echo State Network (ESN), and leak integrator neuron (L-ESN) (Lukosevicius and Jaeger, 2009). Each architecture performs separately an Input Variable Selection (IVS) according to a forward stepwise selection (Anctil et al., 2009) using mean square error as objective function. Post-processing by Predictor Stepwise Selection (PSS) of the super-ensemble has been done following the method proposed by Brochero et al. (2011). IVS results showed that the lagged stream flow, lagged precipitation, and Standardized Precipitation Index (SPI) (McKee et al., 1993) were the most relevant variables. They were respectively selected as one of the firsts three selected variables in 66, 45, and 28 of the 72 scenarios. A relationship between aridity index (Arora, 2002) and NN
He, Wangpeng; Zi, Yanyang; Chen, Binqiang; Wu, Feng; He, Zhengjia
2015-03-01
Mechanical anomaly is a major failure type of induction motor. It is of great value to detect the resulting fault feature automatically. In this paper, an ensemble super-wavelet transform (ESW) is proposed for investigating vibration features of motor bearing faults. The ESW is put forward based on the combination of tunable Q-factor wavelet transform (TQWT) and Hilbert transform such that fault feature adaptability is enabled. Within ESW, a parametric optimization is performed on the measured signal to obtain a quality TQWT basis that best demonstrate the hidden fault feature. TQWT is introduced as it provides a vast wavelet dictionary with time-frequency localization ability. The parametric optimization is guided according to the maximization of fault feature ratio, which is a new quantitative measure of periodic fault signatures. The fault feature ratio is derived from the digital Hilbert demodulation analysis with an insightful quantitative interpretation. The output of ESW on the measured signal is a selected wavelet scale with indicated fault features. It is verified via numerical simulations that ESW can match the oscillatory behavior of signals without artificially specified. The proposed method is applied to two engineering cases, signals of which were collected from wind turbine and steel temper mill, to verify its effectiveness. The processed results demonstrate that the proposed method is more effective in extracting weak fault features of induction motor bearings compared with Fourier transform, direct Hilbert envelope spectrum, different wavelet transforms and spectral kurtosis.
Elliott, E.; Yu, S.; Kooperman, G. J.; Morrison, H.; Wang, M.; Pritchard, M. S.
2014-12-01
Microphysical and resolution sensitivities of explicitly resolved convection within mesoscale convective systems (MCSs) in the central United States are well documented in the context of single case studies simulated by cloud resolving models (CRMs) under tight boundary and initial condition constraints. While such an experimental design allows researchers to causatively isolate the effects of CRM microphysical and resolution parameterizations on modeled MCSs, it is still challenging to produce conclusions generalizable to multiple storms. The uncertainty associated with the results of such experiments comes both from the necessary physical constraints imposed by the limited CRM domain as well as the inability to evaluate or control model internal variability. A computationally practical method to minimize these uncertainties is the use of super-parameterized (SP) global climate models (GCMs), in which CRMs are embedded within GCMs to allow their free interaction with one another as orchestrated by large-scale global dynamics. This study uses NCAR's SP Community Atmosphere Model 5 (SP-CAM5) to evaluate microphysical and horizontal resolution sensitivities in summer ensembles of nocturnal MCSs in the central United States. Storm events within each run were identified using an objective empirical orthogonal function (EOF) algorithm, then further calibrated to harmonize individual storm signals and account for the temporal and spatial heterogeneity between them. Three summers of control data from a baseline simulation are used to assess model internal interannual variability to measure its magnitude relative to sensitivities in a number of distinct experimental runs with varying CRM parameters. Results comparing sensitivities of convective intensity to changes in fall speed assumptions about dense rimed species, one- vs. two-moment microphysics, and CRM horizontal resolution will be discussed.
Re, Matteo; Valentini, Giorgio
2012-03-01
Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been
2002-01-01
NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx
Aken, Bronwen L.; Achuthan, Premanand; Akanni, Wasiu; Amode, M. Ridwan; Bernsdorff, Friederike; Bhai, Jyothish; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Gil, Laurent; Girón, Carlos García; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.; Janacek, Sophie H.; Juettemann, Thomas; Keenan, Stephen; Laird, Matthew R.; Lavidas, Ilias; Maurel, Thomas; McLaren, William; Moore, Benjamin; Murphy, Daniel N.; Nag, Rishi; Newman, Victoria; Nuhn, Michael; Ong, Chuang Kee; Parker, Anne; Patricio, Mateus; Riat, Harpreet Singh; Sheppard, Daniel; Sparrow, Helen; Taylor, Kieron; Thormann, Anja; Vullo, Alessandro; Walts, Brandon; Wilder, Steven P.; Zadissa, Amonida; Kostadima, Myrto; Martin, Fergal J.; Muffato, Matthieu; Perry, Emily; Ruffier, Magali; Staines, Daniel M.; Trevanion, Stephen J.; Cunningham, Fiona; Yates, Andrew; Zerbino, Daniel R.; Flicek, Paul
2017-01-01
Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species. Together, these provide a comprehensive solution for large-scale and targeted genomics applications alike. Among many other developments over the past year, we have improved our resources for gene regulation and comparative genomics, and added CRISPR/Cas9 target sites. We released new browser functionality and tools, including improved filtering and prioritization of genome variation, Manhattan plot visualization for linkage disequilibrium and eQTL data, and an ontology search for phenotypes, traits and disease. We have also enhanced data discovery and access with a track hub registry and a selection of new REST end points. All Ensembl data are freely released to the scientific community and our source code is available via the open source Apache 2.0 license. PMID:27899575
Composed ensembles of random unitary ensembles
Pozniak, M; Kus, M; Pozniak, Marcin; Zyczkowski, Karol; Kus, Marek
1997-01-01
Composed ensembles of random unitary matrices are defined via products of matrices, each pertaining to a given canonical circular ensemble of Dyson. We investigate statistical properties of spectra of some composed ensembles and demonstrate their physical relevance. We discuss also the methods of generating random matrices distributed according to invariant Haar measure on the orthogonal and unitary group.
Super Special Codes using Super Matrices
Kandasamy, W B Vasantha; Ilanthenral, K
2010-01-01
The new classes of super special codes are constructed in this book using the specially constructed super special vector spaces. These codes mainly use the super matrices. These codes can be realized as a special type of concatenated codes. This book has four chapters. In chapter one basic properties of codes and super matrices are given. A new type of super special vector space is constructed in chapter two of this book. Three new classes of super special codes namely, super special row code, super special column code and super special codes are introduced in chapter three. Applications of these codes are given in the final chapter.
Indian Academy of Sciences (India)
D G Hitlin
2006-11-01
Heavy-flavor physics, in particular and physics results from the factories, currently provides strong constraints on models of physics beyond the Standard Model. A new generation of colliders, Super Factories, with 50 to 100 times the luminosity of existing colliders, can, in a dialog with LHC and ILC, provide unique clarification of new physics phenomena seen at those machines.
Exploring ensemble visualization
Phadke, Madhura N.; Pinto, Lifford; Alabi, Oluwafemi; Harter, Jonathan; Taylor, Russell M., II; Wu, Xunlei; Petersen, Hannah; Bass, Steffen A.; Healey, Christopher G.
2012-01-01
An ensemble is a collection of related datasets. Each dataset, or member, of an ensemble is normally large, multidimensional, and spatio-temporal. Ensembles are used extensively by scientists and mathematicians, for example, by executing a simulation repeatedly with slightly different input parameters and saving the results in an ensemble to see how parameter choices affect the simulation. To draw inferences from an ensemble, scientists need to compare data both within and between ensemble members. We propose two techniques to support ensemble exploration and comparison: a pairwise sequential animation method that visualizes locally neighboring members simultaneously, and a screen door tinting method that visualizes subsets of members using screen space subdivision. We demonstrate the capabilities of both techniques, first using synthetic data, then with simulation data of heavy ion collisions in high-energy physics. Results show that both techniques are capable of supporting meaningful comparisons of ensemble data.
Super-stable Poissonian structures
Eliazar, Iddo
2012-10-01
In this paper we characterize classes of Poisson processes whose statistical structures are super-stable. We consider a flow generated by a one-dimensional ordinary differential equation, and an ensemble of particles ‘surfing’ the flow. The particles start from random initial positions, and are propagated along the flow by stochastic ‘wave processes’ with general statistics and general cross correlations. Setting the initial positions to be Poisson processes, we characterize the classes of Poisson processes that render the particles’ positions—at all times, and invariantly with respect to the wave processes—statistically identical to their initial positions. These Poisson processes are termed ‘super-stable’ and facilitate the generalization of the notion of stationary distributions far beyond the realm of Markov dynamics.
Richardson, Thomas M.
2014-01-01
We introduce the super Patalan numbers, a generalization of the super Catalan numbers in the sense of Gessel, and prove a number of properties analagous to those of the super Catalan numbers. The super Patalan numbers generalize the super Catalan numbers similarly to how the Patalan numbers generalize the Catalan numbers.
Making Tree Ensembles Interpretable
Hara, Satoshi; Hayashi, Kohei
2016-01-01
Tree ensembles, such as random forest and boosted trees, are renowned for their high prediction performance, whereas their interpretability is critically limited. In this paper, we propose a post processing method that improves the model interpretability of tree ensembles. After learning a complex tree ensembles in a standard way, we approximate it by a simpler model that is interpretable for human. To obtain the simpler model, we derive the EM algorithm minimizing the KL divergence from the ...
Lessons from Climate Modeling on the Design and Use of Ensembles for Crop Modeling
Wallach, Daniel; Mearns, Linda O.; Ruane, Alexander C.; Roetter, Reimund P.; Asseng, Senthold
2016-01-01
Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.
Multilevel ensemble Kalman filter
Chernov, Alexey
2016-01-06
This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.
The Ensembl REST API: Ensembl Data for Any Language.
Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul
2015-01-01
We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.
Progressive freezing of interacting spins in isolated finite magnetic ensembles
Bhattacharya, Kakoli; Dupuis, Veronique; Le-Roy, Damien; Deb, Pritam
2017-02-01
Self-organization of magnetic nanoparticles into secondary nanostructures provides an innovative way for designing functional nanomaterials with novel properties, different from the constituent primary nanoparticles as well as their bulk counterparts. Collective magnetic properties of such complex closed packing of magnetic nanoparticles makes them more appealing than the individual magnetic nanoparticles in many technological applications. This work reports the collective magnetic behaviour of magnetic ensembles comprising of single domain Fe3O4 nanoparticles. The present work reveals that the ensemble formation is based on the re-orientation and attachment of the nanoparticles in an iso-oriented fashion at the mesoscale regime. Comprehensive dc magnetic measurements show the prevalence of strong interparticle interactions in the ensembles. Due to the close range organization of primary Fe3O4 nanoparticles in the ensemble, the spins of the individual nanoparticles interact through dipolar interactions as realized from remnant magnetization measurements. Signature of super spin glass like behaviour in the ensembles is observed in the memory studies carried out in field cooled conditions. Progressive freezing of spins in the ensembles is corroborated from the Vogel-Fulcher fit of the susceptibility data. Dynamic scaling of relaxation reasserted slow spin dynamics substantiating cluster spin glass like behaviour in the ensembles.
Oza, Nikunj C.
2004-01-01
Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.
National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...
Iba, Yukito
2000-01-01
``Extended Ensemble Monte Carlo''is a generic term that indicates a set of algorithms which are now popular in a variety of fields in physics and statistical information processing. Exchange Monte Carlo (Metropolis-Coupled Chain, Parallel Tempering), Simulated Tempering (Expanded Ensemble Monte Carlo), and Multicanonical Monte Carlo (Adaptive Umbrella Sampling) are typical members of this family. Here we give a cross-disciplinary survey of these algorithms with special emphasis on the great f...
Directory of Open Access Journals (Sweden)
Marin-Garcia Pablo
2010-05-01
Full Text Available Abstract Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.
The semantic similarity ensemble
Directory of Open Access Journals (Sweden)
Andrea Ballatore
2013-12-01
Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.
Wakefield, M. E.
1982-01-01
Protective garment ensemble with internally-mounted environmental- control unit contains its own air supply. Alternatively, a remote-environmental control unit or an air line is attached at the umbilical quick disconnect. Unit uses liquid air that is vaporized to provide both breathing air and cooling. Totally enclosed garment protects against toxic substances.
Music Ensemble: Course Proposal.
Kovach, Brian
A proposal is presented for a Music Ensemble course to be offered at the Community College of Philadelphia for music students who have had previous vocal or instrumental training. A standardized course proposal cover form is followed by a statement of purpose for the course, a list of major course goals, a course outline, and a bibliography. Next,…
DEFF Research Database (Denmark)
Hansen, Lars Kai; Salamon, Peter
1990-01-01
We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....
Multilevel ensemble Kalman filtering
Hoel, Haakon
2016-01-08
The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.
2012-01-01
Get all you need to know with Super Reviews! Each Super Review is packed with in-depth, student-friendly topic reviews that fully explain everything about the subject. The Calculus I Super Review includes a review of functions, limits, basic derivatives, the definite integral, combinations, and permutations. Take the Super Review quizzes to see how much you've learned - and where you need more study. Makes an excellent study aid and textbook companion. Great for self-study!DETAILS- From cover to cover, each in-depth topic review is easy-to-follow and easy-to-grasp - Perfect when preparing for
Algebra & trigonometry super review
2012-01-01
Get all you need to know with Super Reviews! Each Super Review is packed with in-depth, student-friendly topic reviews that fully explain everything about the subject. The Algebra and Trigonometry Super Review includes sets and set operations, number systems and fundamental algebraic laws and operations, exponents and radicals, polynomials and rational expressions, equations, linear equations and systems of linear equations, inequalities, relations and functions, quadratic equations, equations of higher order, ratios, proportions, and variations. Take the Super Review quizzes to see how much y
Application of evolutionary computation on ensemble forecast of quantitative precipitation
Dufek, Amanda S.; Augusto, Douglas A.; Dias, Pedro L. S.; Barbosa, Helio J. C.
2017-09-01
An evolutionary computation algorithm known as genetic programming (GP) has been explored as an alternative tool for improving the ensemble forecast of 24-h accumulated precipitation. Three GP versions and six ensembles' languages were applied to several real-world datasets over southern, southeastern and central Brazil during the rainy period from October to February of 2008-2013. According to the results, the GP algorithms performed better than two traditional statistical techniques, with errors 27-57% lower than simple ensemble mean and the MASTER super model ensemble system. In addition, the results revealed that GP algorithms outperformed the best individual forecasts, reaching an improvement of 34-42%. On the other hand, the GP algorithms had a similar performance with respect to each other and to the Bayesian model averaging, but the former are far more versatile techniques. Although the results for the six ensembles' languages are almost indistinguishable, our most complex linear language turned out to be the best overall proposal. Moreover, some meteorological attributes, including the weather patterns over Brazil, seem to play an important role in the prediction of daily rainfall amount.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Sparked by Super Girl, the androgynous look is in among Chinese youth On September 8, this year's top six contestants on the Super Girl television show, a singing contest for young women, stepped into the spotlight. Nearly none of them had long black hair or wore evening gowns, traditionally associated with beauty in China. Rather, they
Effective Visualization of Temporal Ensembles.
Hao, Lihua; Healey, Christopher G; Bass, Steffen A
2016-01-01
An ensemble is a collection of related datasets, called members, built from a series of runs of a simulation or an experiment. Ensembles are large, temporal, multidimensional, and multivariate, making them difficult to analyze. Another important challenge is visualizing ensembles that vary both in space and time. Initial visualization techniques displayed ensembles with a small number of members, or presented an overview of an entire ensemble, but without potentially important details. Recently, researchers have suggested combining these two directions, allowing users to choose subsets of members to visualization. This manual selection process places the burden on the user to identify which members to explore. We first introduce a static ensemble visualization system that automatically helps users locate interesting subsets of members to visualize. We next extend the system to support analysis and visualization of temporal ensembles. We employ 3D shape comparison, cluster tree visualization, and glyph based visualization to represent different levels of detail within an ensemble. This strategy is used to provide two approaches for temporal ensemble analysis: (1) segment based ensemble analysis, to capture important shape transition time-steps, clusters groups of similar members, and identify common shape changes over time across multiple members; and (2) time-step based ensemble analysis, which assumes ensemble members are aligned in time by combining similar shapes at common time-steps. Both approaches enable users to interactively visualize and analyze a temporal ensemble from different perspectives at different levels of detail. We demonstrate our techniques on an ensemble studying matter transition from hadronic gas to quark-gluon plasma during gold-on-gold particle collisions.
Nonlinear Super Integrable Couplings of Super Classical-Boussinesq Hierarchy
Directory of Open Access Journals (Sweden)
Xiuzhi Xing
2014-01-01
Full Text Available Nonlinear integrable couplings of super classical-Boussinesq hierarchy based upon an enlarged matrix Lie super algebra were constructed. Then, its super Hamiltonian structures were established by using super trace identity. As its reduction, nonlinear integrable couplings of the classical integrable hierarchy were obtained.
Imprinting and recalling cortical ensembles.
Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S; Yuste, Rafael
2016-08-12
Neuronal ensembles are coactive groups of neurons that may represent building blocks of cortical circuits. These ensembles could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations from ensembles in the visual cortex of awake mice builds neuronal ensembles that recur spontaneously after being imprinted and do not disrupt preexisting ones. Moreover, imprinted ensembles can be recalled by single- cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. Copyright © 2016, American Association for the Advancement of Science.
DEFF Research Database (Denmark)
Nasrollahi, Kamal; Moeslund, Thomas B.
2014-01-01
Super-resolution, the process of obtaining one or more high-resolution images from one or more low-resolution observations, has been a very attractive research topic over the last two decades. It has found practical applications in many real world problems in different fields, from satellite...... the contributions of different authors to the basic concepts of each group. Furthermore, common issues in super-resolution algorithms, such as imaging models and registration algorithms, optimization of the cost functions employed, dealing with color information, improvement factors, assessment of super...
Multilevel ensemble Kalman filtering
Hoel, Hakon
2016-06-14
This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Critical behavior in topological ensembles
Bulycheva, K; Nechaev, S
2014-01-01
We consider the relation between three physical problems: 2D directed lattice random walks in an external magnetic field, ensembles of torus knots, and 5d Abelian SUSY gauge theory with massless hypermultiplet in $\\Omega$ background. All these systems exhibit the critical behavior typical for the "area+length" statistics of grand ensembles of 2D directed paths. In particular, using the combinatorial description, we have found the new critical behavior in the ensembles of the torus knots and in the instanton ensemble in 5d gauge theory. The relation with the integrable model is discussed.
Random matrix theory for mixed regular-chaotic dynamics in the super-extensive regime
El-Hady, A Abd
2011-01-01
We apply Tsallis's q-indexed nonextensive entropy to formulate a random matrix theory (RMT), which may be suitable for systems with mixed regular-chaotic dynamics. We consider the super-extensive regime of q < 1. We obtain analytical expressions for the level-spacing distributions, which are strictly valid for 2 \\times 2 random-matrix ensembles, as usually done in the standard RMT. We compare the results with spacing distributions, numerically calculated for random matrix ensembles describing a harmonic oscillator perturbed by Gaussian orthogonal and unitary ensembles.
Federal Laboratory Consortium — The NETL Super Computer was designed for performing engineering calculations that apply to fossil energy research. It is one of the world’s larger supercomputers,...
DEFF Research Database (Denmark)
Nasrollahi, Kamal; Moeslund, Thomas B.
2014-01-01
and aerial imaging to medical image processing, to facial image analysis, text image analysis, sign and number plates reading, and biometrics recognition, to name a few. This has resulted in many research papers, each developing a new super-resolution algorithm for a specific purpose. The current......Super-resolution, the process of obtaining one or more high-resolution images from one or more low-resolution observations, has been a very attractive research topic over the last two decades. It has found practical applications in many real world problems in different fields, from satellite...... the contributions of different authors to the basic concepts of each group. Furthermore, common issues in super-resolution algorithms, such as imaging models and registration algorithms, optimization of the cost functions employed, dealing with color information, improvement factors, assessment of super...
Magro, Lluís Martí
2016-06-01
The Super-Kamiokande experiment performs a large variety of studies, many of them in the neutrino sector. The archetypes are atmospheric neutrino (recently awarded with the Nobel prize for Mr. T. Kajita) and the solar neutrinos analyses. In these proceedings we report our latest results and present updates to indirect dark matter searches, our solar neutrino analysis and discuss the future upgrade of Super-Kamiokande by loading gadolinium into our ultra-pure water.
Institute of Scientific and Technical Information of China (English)
WANG PEI
2006-01-01
@@ In recent years, Changsha,the capital city of Hunan Province, has become famous across China for its innovative TV channel, in particular the cultural phenomenon of the Super Girl talent show. And as far as culture goes, Hunan TV is merely a reflection of a renaissance happening in the city. Animation, music halls, drama festivals and a famous book market are just some of the city's cultural sectors that are benefiting from the fame and notoriety of the Super Girl show.
Tenorio-Tagle, G
1980-01-01
The author has calculated the collision of a small neutral cloud (surface density approximately 10/sup 19/ cm/sup -2/) with a constant density galactic disk. Through the collision, a large amount of energy is deposited in a small volume of the galaxy, resulting in a supersonic expansion of very hot (10/sup 6/-10/sup 7/K) gas into the Galaxy and out of the galactic disk. The expansion generates a large cavity (a super-ring) with physical characteristics (diameter, velocity of expansion, etc.) in agreement with the observations, and a large volume of hot low-density gas with properties similar to those of the observed coronal gas. (31 refs).
Nonlinear Super Integrable Couplings of Super Dirac Hierarchy and Its Super Hamiltonian Structures
Institute of Scientific and Technical Information of China (English)
尤福财
2012-01-01
We construct nonlinear super integrable couplings of the super integrable Dirac hierarchy based on an enlarged matrix Lie superalgebra. Then its super Hamiltonian structure is furnished by super trace identity. As its reduction, we gain the nonlinear integrable couplings of the classical integrable Dirac hierarchy.
Thermal properties for an ensemble of polymer Fermi oscillators
Chacón-Acosta, Guillermo; García-Chung, Angel A.; Hernandez-Hernandez, Héctor H.
2015-11-01
Polymer quantum mechanics is a model inspired on loop quantum gravity in which one can study, in a simplified way, some properties of certain quantum mechanical models. There is a length parameter in this model, known as the polymer scale, comprising the discreteness introduced in this particular quantization. There is a recent analysis on quantum fields where the Fermi oscillator is polymerized by means of a non-analytic representation of the corresponding Weyl super-algebra, its energy spectrum acquires modifications by the introduction of polymer parameters, which turn out to be super-numbers. In this work we present the first step in studying thermostatistical properties of an ensemble of Fermi oscillators. As an initial approximation we consider the polymer parameters as real deviations from their usual values. We obtain modifications to the thermal properties of the system in terms of polymer parameters. In the last section we critically discuss the possible physical significance of the results.
ESPC Coupled Global Ensemble Design
2014-09-30
coupled system infrastructure and forecasting capabilities. Initial operational capability is targeted for 2018. APPROACH 1. It is recognized...provided will be the probability distribution function (PDF) of environmental conditions. It is expected that this distribution will have skill. To...system would be the initial capability for ensemble forecasts . Extensions to fully coupled ensembles would be the next step. 2. Develop an extended
Deforming super Riemann surfaces with gravitinos and super Schottky groups
Energy Technology Data Exchange (ETDEWEB)
Playle, Sam [Dipartimento di Fisica, Università di Torino and INFN, Sezione di Torino,Via P. Giuria 1, I-10125 Torino (Italy)
2016-12-12
The (super) Schottky uniformization of compact (super) Riemann surfaces is briefly reviewed. Deformations of super Riemann surface by gravitinos and Beltrami parameters are recast in terms of super Schottky group cohomology. It is checked that the super Schottky group formula for the period matrix of a non-split surface matches its expression in terms of a gravitino and Beltrami parameter on a split surface. The relationship between (super) Schottky groups and the construction of surfaces by gluing pairs of punctures is discussed in an appendix.
Botnet analysis using ensemble classifier
Directory of Open Access Journals (Sweden)
Anchit Bijalwan
2016-09-01
Full Text Available This paper analyses the botnet traffic using Ensemble of classifier algorithm to find out bot evidence. We used ISCX dataset for training and testing purpose. We extracted the features of both training and testing datasets. After extracting the features of this dataset, we bifurcated these features into two classes, normal traffic and botnet traffic and provide labelling. Thereafter using modern data mining tool, we have applied ensemble of classifier algorithm. Our experimental results show that the performance for finding bot evidence using ensemble of classifiers is better than single classifier. Ensemble based classifiers perform better than single classifier by either combining powers of multiple algorithms or introducing diversification to the same classifier by varying input in bot analysis. Our results are showing that by using voting method of ensemble based classifier accuracy is increased up to 96.41% from 93.37%.
On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles
Luo, Xiaodong
2010-09-19
The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].
Directory of Open Access Journals (Sweden)
Fernando Mainardi Fan
2015-09-01
New hydrological insights for the region: This work presents one of the first extensive efforts to evaluate ensemble forecasts for large-scale basins in South America using TIGGE archive data. Results from these scenarios provide validation criteria and confirm that ensemble forecasts depend on the particular EPS used to run the hydrological model and on the basin studied. Furthermore, the use of the Super Ensemble seems to be a good strategy in terms of performance and robustness. The importance of the TIGGE database is also highlighted.
Dennis, Andrew K
2013-01-01
This book follows a step-by-step, tutorial-based approach which will teach you how to develop your own super cluster using Raspberry Pi computers quickly and efficiently.Raspberry Pi Super Cluster is an introductory guide for those interested in experimenting with parallel computing at home. Aimed at Raspberry Pi enthusiasts, this book is a primer for getting your first cluster up and running.Basic knowledge of C or Java would be helpful but no prior knowledge of parallel computing is necessary.
DEFF Research Database (Denmark)
Gorshkov, Vladimir; Verano-Braga, Thiago; Kjeldsen, Frank
2015-01-01
SuperQuant is a quantitative proteomics data processing approach that uses complementary fragment ions to identify multiple co-isolated peptides in tandem mass spectra allowing for their quantification. This approach can be applied to any shotgun proteomics data set acquired with high mass accura...... of the same proteins were close to the values typical for other precursor ion-based quantification methods. The raw data is deposited to ProteomeXchange (PXD001907). The developed node is available for testing at https://github.com/caetera/SuperQuantNode....
Ensemble manifold regularization.
Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng
2012-06-01
We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.
Diurnal Ensemble Surface Meteorology Statistics
U.S. Environmental Protection Agency — Excel file containing diurnal ensemble statistics of 2-m temperature, 2-m mixing ratio and 10-m wind speed. This Excel file contains figures for Figure 2 in the...
DEFF Research Database (Denmark)
2004-01-01
Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output...... is available via two password-protected web-pages hosted at IMM and is used daily by Elsam and E2....
Similarity measures for protein ensembles
DEFF Research Database (Denmark)
Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper
2009-01-01
Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations...... a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single...
DEFF Research Database (Denmark)
2004-01-01
Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output is a...... is available via two password-protected web-pages hosted at IMM and is used daily by Elsam and E2....
CERN PhotoLab
1975-01-01
Remotely controlled re-entrant vacuum vessels, with very thin (0.17 mm) central windows, that will be installed in each downstream arm of intersection I-8. Detectors for a coming physics experiment, placed inside these "Super Roman Pots", can be moved very close to the circulating ISR beams.
1975-01-01
Remotely controlled re-entrant vacuum vessels, with very thin (0.17 mm) central windows, that were installed in each downstream arm of the ISR intersection I-8. Detectors placed inside these Super Roman Pots could be moved very close to the circulating ISR beams. (See Annual Report 1974 p. 110.)
RumEnKF: running very large Ensembles Kalman Filter by forgetting what you just did.
Hut, R.; Amisigo, B. A.; Steele-Dunne, S. C.; Van De Giesen, N.
2014-12-01
The eWaterCycle project works towards running an operational hyper-resolution hydrological global model, assimilating incoming satellite data in real time, and making 14 day predictions of floods and droughts. A problem encountered in the eWatercycle project is that the computer memory needed to store a single ensemble member becomes so large that storing enough ensembles to run the EnKF is impossible, even when using mitigating strategies such as covariance inflation or localization. Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF) is introduced as a variant on the Ensemble Kalman Filter (EnKF). RumEnKF differs from EnKF in that it does not store the entire ensemble, but rather only saves the first two moments of the ensemble distribution. In this way, the number of ensemble members that can be calculated is less dependent on available memory, and mainly on available computing power (CPU). RumEnKF is developed to make optimal use of current generation super computer architecture, where the number of available floating point operations (flops) increases more rapidly than the available memory and where inter-node communication can quickly become a bottleneck. In this presentation, two simple models are used (auto-regressive and Lorenz) to show that RumEnKF performs similar to the EnKF. Furthermore, it is also shown that increasing the ensemble size has a similar impact on the estimation error from the two algorithms In this preliminary results, RumEnKF reduces the used memory compared to the EnKF when the number of ensemble members is greater than half the number of state variables. Future research will focus on strategies to further reduce the memory burden of running non-linear data assimilation on very large models.
Lei, Lili; Whitaker, Jeffrey S.
2017-06-01
The current NCEP operational four-dimensional ensemble-variational data assimilation system uses a control forecast at T1534 resolution coupled with an 80 member ensemble at T574 resolution. Given an increase in computing resources, and assuming the control forecast resolution is fixed, would it be better to increase the ensemble size and keep the ensemble resolution the same, or increase the ensemble resolution and keep the ensemble size the same? To answer this question, experiments are conducted at reduced resolutions. Two sets of experiments are conducted which both use approximately four times more computational resources than the control experiment that uses a control forecast at T670 and an 80 member ensemble at T254. One increases the ensemble size to 320 but keeps the ensemble resolution at T254; and the other increases the ensemble resolution to T670 but retains an 80 ensemble size. When ensemble size increases to 320, turning off the static component of the background-error covariance does not degrade performance. When the data assimilation parameters are tuned for optimal performance, increasing either ensemble size or ensemble resolution can improve the forecast performance. Increasing ensemble resolution is slightly, but significantly better than increasing ensemble size for these experiments, particularly when considering errors at smaller scales. Much of the benefit of increasing ensemble resolution comes about by eliminating the need for a deterministic control forecast and running all of the background forecasts at the same resolution. In this "single-resolution" mode, the control forecast is replaced by an ensemble average, which reduces small-scale errors significantly.
DEFF Research Database (Denmark)
Stylianidou, Stella; Brennan, Connor; Nissen, Silas B
2016-01-01
-colonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter, and neighboring cells......Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well......-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment micro...
Algorithms on ensemble quantum computers.
Boykin, P Oscar; Mor, Tal; Roychowdhury, Vwani; Vatan, Farrokh
2010-06-01
In ensemble (or bulk) quantum computation, all computations are performed on an ensemble of computers rather than on a single computer. Measurements of qubits in an individual computer cannot be performed; instead, only expectation values (over the complete ensemble of computers) can be measured. As a result of this limitation on the model of computation, many algorithms cannot be processed directly on such computers, and must be modified, as the common strategy of delaying the measurements usually does not resolve this ensemble-measurement problem. Here we present several new strategies for resolving this problem. Based on these strategies we provide new versions of some of the most important quantum algorithms, versions that are suitable for implementing on ensemble quantum computers, e.g., on liquid NMR quantum computers. These algorithms are Shor's factorization algorithm, Grover's search algorithm (with several marked items), and an algorithm for quantum fault-tolerant computation. The first two algorithms are simply modified using a randomizing and a sorting strategies. For the last algorithm, we develop a classical-quantum hybrid strategy for removing measurements. We use it to present a novel quantum fault-tolerant scheme. More explicitly, we present schemes for fault-tolerant measurement-free implementation of Toffoli and σ(z)(¼) as these operations cannot be implemented "bitwise", and their standard fault-tolerant implementations require measurement.
CME Ensemble Forecasting - A Primer
Pizzo, V. J.; de Koning, C. A.; Cash, M. D.; Millward, G. H.; Biesecker, D. A.; Codrescu, M.; Puga, L.; Odstrcil, D.
2014-12-01
SWPC has been evaluating various approaches for ensemble forecasting of Earth-directed CMEs. We have developed the software infrastructure needed to support broad-ranging CME ensemble modeling, including composing, interpreting, and making intelligent use of ensemble simulations. The first step is to determine whether the physics of the interplanetary propagation of CMEs is better described as chaotic (like terrestrial weather) or deterministic (as in tsunami propagation). This is important, since different ensemble strategies are to be pursued under the two scenarios. We present the findings of a comprehensive study of CME ensembles in uniform and structured backgrounds that reveals systematic relationships between input cone parameters and ambient flow states and resulting transit times and velocity/density amplitudes at Earth. These results clearly indicate that the propagation of single CMEs to 1 AU is a deterministic process. Thus, the accuracy with which one can forecast the gross properties (such as arrival time) of CMEs at 1 AU is determined primarily by the accuracy of the inputs. This is no tautology - it means specifically that efforts to improve forecast accuracy should focus upon obtaining better inputs, as opposed to developing better propagation models. In a companion paper (deKoning et al., this conference), we compare in situ solar wind data with forecast events in the SWPC operational archive to show how the qualitative and quantitative findings presented here are entirely consistent with the observations and may lead to improved forecasts of arrival time at Earth.
Estimating preselected and postselected ensembles
Energy Technology Data Exchange (ETDEWEB)
Massar, Serge [Laboratoire d' Information Quantique, C.P. 225, Universite libre de Bruxelles (U.L.B.), Av. F. D. Rooselvelt 50, B-1050 Bruxelles (Belgium); Popescu, Sandu [H. H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol BS8 1TL (United Kingdom); Hewlett-Packard Laboratories, Stoke Gifford, Bristol BS12 6QZ (United Kingdom)
2011-11-15
In analogy with the usual quantum state-estimation problem, we introduce the problem of state estimation for a pre- and postselected ensemble. The problem has fundamental physical significance since, as argued by Y. Aharonov and collaborators, pre- and postselected ensembles are the most basic quantum ensembles. Two new features are shown to appear: (1) information is flowing to the measuring device both from the past and from the future; (2) because of the postselection, certain measurement outcomes can be forced never to occur. Due to these features, state estimation in such ensembles is dramatically different from the case of ordinary, preselected-only ensembles. We develop a general theoretical framework for studying this problem and illustrate it through several examples. We also prove general theorems establishing that information flowing from the future is closely related to, and in some cases equivalent to, the complex conjugate information flowing from the past. Finally, we illustrate our approach on examples involving covariant measurements on spin-1/2 particles. We emphasize that all state-estimation problems can be extended to the pre- and postselected situation. The present work thus lays the foundations of a much more general theory of quantum state estimation.
Institute of Scientific and Technical Information of China (English)
LU Huijuan; Qin XU; YAO Mingming; GAO Shouting
2011-01-01
By sampling perturbed state vectors from each ensenble prediction run at properly selected time levels in the vicinity of the analysis time, the recently proposed time-expanded sampling approach can enlarge the ensemble size without increasing the number of prediction runs and, hence, can reduce the computational cost of an ensemble-based filter. In this study, this approach is tested for the first time with real radar data from a tornadic thunderstorm. In particular, four assimilation experiments were performed to test the time-expanded sampling method against the conventional ensemble sampling method used by ensemblebased filters. In these experiments, the ensemble square-root filter (EnSRF) was used with 45 ensemble members generated by the time-expanded sampling and conventional sampling from 15 and 45 prediction runs, respectively, and quality-controlled radar data were compressed into super-observations with properly reduced spatial resolutions to improve the EnSRF performances. The results show that the time-expanded sampling approach not only can reduce the computational cost but also can improve the accuracy of the analysis, especially when the ensemble size is severely limited due to computational constraints for real-radar data assimilation. These potential merits are consistent with those previously demonstrated by assimilation experiments with simulated data.
Fairbrother, Debbie
2017-01-01
NASA is in the process of qualifying the mid-size Super Pressure Balloon (SPB) to provide constant density altitude flight for science investigations at polar and mid-latitudes. The status of the development of the 18.8 million cubic foot SPB capable of carrying one-tone of science to 110,000 feet, will be given. In addition, the operating considerations such as launch sites, flight safety considerations, and recovery will be discussed.
Crul, M.R.J.; Schneider, J.; Lelie, F.
2013-01-01
Le concept de super-diversité, en cernant les conditions d'un scénario 'avenir optimiste, offre un nouvel éclairage au débat sur l'intégration. Nous sommes à la croisée des chemins. Cette étude comparative internationale montre qu'un avenir souriant se profile dans les villes qui donnent des chances
Performing the Super Instrument
DEFF Research Database (Denmark)
Kallionpaa, Maria
2016-01-01
The genre of contemporary classical music has seen significant innovation and research related to new super, hyper, and hybrid instruments, which opens up a vast palette of expressive potential. An increasing number of composers, performers, instrument designers, engineers, and computer programmers...... provides the performer extensive virtuoso capabilities in terms of instrumental range, harmony, timbre, or spatial, textural, acoustic, technical, or technological qualities. The discussion will be illustrated by a composition case study involving augmented musical instrument electromagnetic resonator...
Performing the Super Instrument
DEFF Research Database (Denmark)
Kallionpaa, Maria
2016-01-01
provides the performer extensive virtuoso capabilities in terms of instrumental range, harmony, timbre, or spatial, textural, acoustic, technical, or technological qualities. The discussion will be illustrated by a composition case study involving augmented musical instrument electromagnetic resonator......The genre of contemporary classical music has seen significant innovation and research related to new super, hyper, and hybrid instruments, which opens up a vast palette of expressive potential. An increasing number of composers, performers, instrument designers, engineers, and computer programmers...
Directory of Open Access Journals (Sweden)
Valencia D.
2011-02-01
Full Text Available The era of Super-Earths has formally begun with the detection of transiting low-mass exoplanets CoRoT-7b and GJ 1214b. In the path of characterising super-Earths, the ﬁrst step is to infer their composition. While the discovery data for CoRoT-7b, in combination with the high atmospheric mass loss rate inferred from the high insolation, suggested that it was a rocky planet, the new proposed mass values have widened the possibilities. The combined mass range 1−10 M⊕ allows for a volatile-rich (and requires it if the mass is less than 4 M⊕ , an Earth-like or a super-Mercury-like composition. In contrast, the radius of GJ 1214b is too large to admit a solid composition, thus it necessarily to have a substantial gas layer. Some evidence suggests that within this gas layer H/He is a small but non-negligible component. These two planets are the ﬁrst of many transiting low-mass exoplanets expected to be detected and they exemplify the limitations faced when inferring composition, which come from the degenerate character of the problem and the large error bars in the data.
Super Fuzzy Matrices and Super Fuzzy Models for Social Scientists
Kandasamy, W B Vasantha; Amal, K
2008-01-01
This book introduces the concept of fuzzy super matrices and operations on them. This book will be highly useful to social scientists who wish to work with multi-expert models. Super fuzzy models using Fuzzy Cognitive Maps, Fuzzy Relational Maps, Bidirectional Associative Memories and Fuzzy Associative Memories are defined here. The authors introduce 13 multi-expert models using the notion of fuzzy supermatrices. These models are described with illustrative examples. This book has three chapters. In the first chaper, the basic concepts about super matrices and fuzzy super matrices are recalled. Chapter two introduces the notion of fuzzy super matrices adn their properties. The final chapter introduces many super fuzzy multi expert models.
Super-quantum curves from super-eigenvalue models
Ciosmak, Paweł; Manabe, Masahide; Sułkowski, Piotr
2016-01-01
In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce $\\beta$-deformed version of those models, and derive differential equations for associated $\\alpha/\\beta$-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.
Super-quantum curves from super-eigenvalue models
Ciosmak, Paweł; Hadasz, Leszek; Manabe, Masahide; Sułkowski, Piotr
2016-10-01
In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/ β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.
Super-quantum curves from super-eigenvalue models
Energy Technology Data Exchange (ETDEWEB)
Ciosmak, Paweł [Faculty of Mathematics, Informatics and Mechanics, University of Warsaw,ul. Banacha 2, 02-097 Warsaw (Poland); Hadasz, Leszek [M. Smoluchowski Institute of Physics, Jagiellonian University,ul. Łojasiewicza 11, 30-348 Kraków (Poland); Manabe, Masahide [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Sułkowski, Piotr [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E. California Blvd, Pasadena, CA 91125 (United States)
2016-10-10
In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.
Linking neuronal ensembles by associative synaptic plasticity.
Directory of Open Access Journals (Sweden)
Qi Yuan
Full Text Available Synchronized activity in ensembles of neurons recruited by excitatory afferents is thought to contribute to the coding information in the brain. However, the mechanisms by which neuronal ensembles are generated and modified are not known. Here we show that in rat hippocampal slices associative synaptic plasticity enables ensembles of neurons to change by incorporating neurons belonging to different ensembles. Associative synaptic plasticity redistributes the composition of different ensembles recruited by distinct inputs such as to specifically increase the similarity between the ensembles. These results show that in the hippocampus, the ensemble of neurons recruited by a given afferent projection is fluid and can be rapidly and persistently modified to specifically include neurons from different ensembles. This linking of ensembles may contribute to the formation of associative memories.
A mollified Ensemble Kalman filter
Bergemann, Kay
2010-01-01
It is well recognized that discontinuous analysis increments of sequential data assimilation systems, such as ensemble Kalman filters, might lead to spurious high frequency adjustment processes in the model dynamics. Various methods have been devised to continuously spread out the analysis increments over a fixed time interval centered about analysis time. Among these techniques are nudging and incremental analysis updates (IAU). Here we propose another alternative, which may be viewed as a hybrid of nudging and IAU and which arises naturally from a recently proposed continuous formulation of the ensemble Kalman analysis step. A new slow-fast extension of the popular Lorenz-96 model is introduced to demonstrate the properties of the proposed mollified ensemble Kalman filter.
Excitation energies from ensemble DFT
Borgoo, Alex; Teale, Andy M.; Helgaker, Trygve
2015-12-01
We study the evaluation of the Gross-Oliveira-Kohn expression for excitation energies E1-E0=ɛ1-ɛ0+∂E/xc,w[ρ] ∂w | ρ =ρ0. This expression gives the difference between an excitation energy E1 - E0 and the corresponding Kohn-Sham orbital energy difference ɛ1 - ɛ0 as a partial derivative of the exchange-correlation energy of an ensemble of states Exc,w[ρ]. Through Lieb maximisation, on input full-CI density functions, the exchange-correlation energy is evaluated accurately and the partial derivative is evaluated numerically using finite difference. The equality is studied numerically for different geometries of the H2 molecule and different ensemble weights. We explore the adiabatic connection for the ensemble exchange-correlation energy. The latter may prove useful when modelling the unknown weight dependence of the exchange-correlation energy.
The Partition Ensemble Fallacy Fallacy
Nemoto, K; Nemoto, Kae; Braunstein, Samuel L.
2002-01-01
The Partition Ensemble Fallacy was recently applied to claim no quantum coherence exists in coherent states produced by lasers. We show that this claim relies on an untestable belief of a particular prior distribution of absolute phase. One's choice for the prior distribution for an unobservable quantity is a matter of `religion'. We call this principle the Partition Ensemble Fallacy Fallacy. Further, we show an alternative approach to construct a relative-quantity Hilbert subspace where unobservability of certain quantities is guaranteed by global conservation laws. This approach is applied to coherent states and constructs an approximate relative-phase Hilbert subspace.
Multimodel ensembles of wheat growth
DEFF Research Database (Denmark)
Martre, Pierre; Wallach, Daniel; Asseng, Senthold
2015-01-01
, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24...
Global Ensemble Forecast System (GEFS) [1 Deg.
National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...
Super insulating aerogel glazing
DEFF Research Database (Denmark)
Schultz, Jørgen Munthe; Jensen, Karsten Ingerslev; Kristiansen, Finn Harken
2004-01-01
Monolithic silica aerogel offers the possibility of combining super insulation and high solar energy transmittance, which has been the background for a previous and a current EU project on research and development of monolithic silica aerogel as transparent insulation in windows. Generally, windows...... form the weakest part of the thermal envelope with respect to heat loss coefficient, but on the other hand also play an important role for passive solar energy utilisation. For window orientations other than south, the net energy balance will be close to or below zero. However, the properties...
Super insulating aerogel glazing
DEFF Research Database (Denmark)
Schultz, Jørgen Munthe; Jensen, Karsten Ingerslev; Kristiansen, Finn Harken
2005-01-01
This paper describes the application results of a previous and current EU-project on super insulating glazing based on monolithic silica aerogel. Prototypes measuring approx. 55´55 cm2 have been made with 15 mm evacuated aerogel between two layers of low-iron glass. Anti-reflective treatment...... of the glass and a heat-treatment of the aerogel increases the visible quality and the solar energy transmittance. A low-conductive rim seal solution with the required vacuum barrier properties has been developed along with a reliable assembly and evacuation process. The prototypes have a centre heat loss...
Zeng, Wangdong
2016-05-30
The challenging synthesis of a laterally extended heptazethrene molecule, the super-heptazethrene derivative SHZ-CF3, is reported. This molecule was prepared using a strategy involving a multiple selective intramolecular Friedel–Crafts alkylation followed by oxidative dehydrogenation. Compound SHZ-CF3 exhibits an open-shell singlet diradical ground state with a much larger diradical character compared with the heptazethrene derivatives. An intermediate dibenzo-terrylene SHZ-2H was also obtained during the synthesis. This study provides a new synthetic method to access large-size quinoidal polycyclic hydrocarbons with unique physical properties.
Directory of Open Access Journals (Sweden)
J. Dietrich
2009-08-01
Full Text Available Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydro-meteorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average super-ensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.
Squeezing of Collective Excitations in Spin Ensembles
DEFF Research Database (Denmark)
Kraglund Andersen, Christian; Mølmer, Klaus
2012-01-01
We analyse the possibility to create two-mode spin squeezed states of two separate spin ensembles by inverting the spins in one ensemble and allowing spin exchange between the ensembles via a near resonant cavity field. We investigate the dynamics of the system using a combination of numerical an...
Quantitative super-resolution microscopy
Harkes, Rolf
2016-01-01
Super-Resolution Microscopy is an optical fluorescence technique. In this thesis we focus on single molecule super-resolution, where the position of single molecules is determined. Typically these molecules can be localized with a 10 to 30nm precision. This technique is applied in four different s
Classical and Quantum Ensembles via Multiresolution. II. Wigner Ensembles
2004-01-01
We present the application of the variational-wavelet analysis to the analysis of quantum ensembles in Wigner framework. (Naive) deformation quantization, the multiresolution representations and the variational approach are the key points. We construct the solutions of Wigner-like equations via the multiscale expansions in the generalized coherent states or high-localized nonlinear eigenmodes in the base of the compactly supported wavelets and the wavelet packets. We demonstrate the appearanc...
Hydrological Ensemble Prediction System (HEPS)
Thielen-Del Pozo, J.; Schaake, J.; Martin, E.; Pailleux, J.; Pappenberger, F.
2010-09-01
Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Following on the success of the use of ensembles for weather forecasting, the hydrological community now moves increasingly towards Hydrological Ensemble Prediction Systems (HEPS) for improved flood forecasting using operationally available NWP products as inputs. However, these products are often generated on relatively coarse scales compared to hydrologically relevant basin units and suffer systematic biases that may have considerable impact when passed through the non-linear hydrological filters. Therefore, a better understanding on how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes is necessary. The "Hydrologic Ensemble Prediction Experiment" (HEPEX), is an international initiative consisting of hydrologists, meteorologist and end-users to advance probabilistic hydrologic forecast techniques for flood, drought and water management applications. Different aspects of the hydrological ensemble processor are being addressed including • Production of useful meteorological products relevant for hydrological applications, ranging from nowcasting products to seasonal forecasts. The importance of hindcasts that are consistent with the operational weather forecasts will be discussed to support bias correction and downscaling, statistically meaningful verification of HEPS, and the development and testing of operating rules; • Need for downscaling and post-processing of weather ensembles to reduce bias before entering hydrological applications; • Hydrological model and parameter uncertainty and how to correct and
Spectral diagonal ensemble Kalman filters
Kasanický, Ivan; Vejmelka, Martin
2015-01-01
A new type of ensemble Kalman filter is developed, which is based on replacing the sample covariance in the analysis step by its diagonal in a spectral basis. It is proved that this technique improves the aproximation of the covariance when the covariance itself is diagonal in the spectral basis, as is the case, e.g., for a second-order stationary random field and the Fourier basis. The method is extended by wavelets to the case when the state variables are random fields, which are not spatially homogeneous. Efficient implementations by the fast Fourier transform (FFT) and discrete wavelet transform (DWT) are presented for several types of observations, including high-dimensional data given on a part of the domain, such as radar and satellite images. Computational experiments confirm that the method performs well on the Lorenz 96 problem and the shallow water equations with very small ensembles and over multiple analysis cycles.
Symanzik flow on HISQ ensembles
Bazavov, A; Brown, N; DeTar, C; Foley, J; Gottlieb, Steven; Heller, U M; Hetrick, J E; Laiho, J; Levkova, L; Oktay, M; Sugar, R L; Toussaint, D; Van de Water, R S; Zhou, R
2013-01-01
We report on a scale determination with gradient-flow techniques on the $N_f = 2 + 1 + 1$ HISQ ensembles generated by the MILC collaboration. The lattice scale $w_0/a$, originally proposed by the BMW collaboration, is computed using Symanzik flow at four lattice spacings ranging from 0.15 to 0.06 fm. With a Taylor series ansatz, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. We give a preliminary determination of the scale $w_0$ in physical units, along with associated systematic errors, and compare with results from other groups. We also present a first estimate of autocorrelation lengths as a function of flowtime for these ensembles.
Statistical Analysis of Protein Ensembles
Máté, Gabriell; Heermann, Dieter
2014-04-01
As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.
Statistical Analysis of Protein Ensembles
Directory of Open Access Journals (Sweden)
Gabriell eMáté
2014-04-01
Full Text Available As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.
Super insulating aerogel glazing
DEFF Research Database (Denmark)
Schultz, Jørgen Munthe; Jensen, Karsten Ingerslev; Kristiansen, Finn Harken
2004-01-01
Monolithic silica aerogel offers the possibility of combining super insulation and high solar energy transmittance, which has been the background for a previous and a current EU project on research and development of monolithic silica aerogel as transparent insulation in windows. Generally, windows...... form the weakest part of the thermal envelope with respect to heat loss coefficient, but on the other hand also play an important role for passive solar energy utilisation. For window orientations other than south, the net energy balance will be close to or below zero. However, the properties...... of aerogel glazing will allow for a positive net energy gain even for north facing vertical windows in a Danish climate during the heating season. This means that high quality daylight can be obtained even with additional energy gain. On behalf of the partners of the two EU projects, results related...
Xinjiang Girl World Super Model
Institute of Scientific and Technical Information of China (English)
1999-01-01
Leading Chinese model Yue Mei won thetitle of World Super Model at the ’98 WorldSuper Model Competition held in FranceSeptember 6 - 17. Yue, a university studentfrom the Xinjiang Uygur AutonomousRegion, had won the top title at ’98 ChinaSuper Model Competition held in Beijingone month earier.After that, she underwentone month’s professional modeling trainingwith the New Silk Road ModelingManagement Company before setting off forthe world competition. In France, Yueimpressed the judges with her strikingfeatures, and display of oriental elegance and
Classical and Quantum Ensembles via Multiresolution. II. Wigner Ensembles
Fedorova, A N; Fedorova, Antonina N.; Zeitlin, Michael G.
2004-01-01
We present the application of the variational-wavelet analysis to the analysis of quantum ensembles in Wigner framework. (Naive) deformation quantization, the multiresolution representations and the variational approach are the key points. We construct the solutions of Wigner-like equations via the multiscale expansions in the generalized coherent states or high-localized nonlinear eigenmodes in the base of the compactly supported wavelets and the wavelet packets. We demonstrate the appearance of (stable) localized patterns (waveletons) and consider entanglement and decoherence as possible applications.
SuperB Progress Reports Accelerator
Biagini, Maria Enrica; Boscolo, M; Buonomo, B; Demma, T; Drago, A; Esposito, M; Guiducci, S; Mazzitelli, G; Pellegrino, L; Preger, M A; Raimondi, P; Ricci, R; Rotundo, U; Sanelli, C; Serio, M; Stella, A; Tomassini, S; Zobov, M; Bertsche, K; Brachman, A; Cai, Y; Chao, A; Chesnut, R; Donald, M.H; Field, C; Fisher, A; Kharakh, D; Krasnykh, A; Moffeit, K; Nosochkov, Y; Pivi, M; Seeman, J; Sullivan, M.K; Weathersby, S; Weidemann, A; Weisend, J; Wienands, U; Wittmer, W; Woods, M; Yocky, G; Bogomiagkov, A; Koop, I; Levichev, E; Nikitin, S; Okunev, I; Piminov, P; Sinyatkin, S; Shatilov, D; Vobly, P; Bosi, F; Liuzzo, S; Paoloni, E; Bonis, J; Chehab, R; Le Meur, G; Lepercq, P; Letellier-Cohen, F; Mercier, B; Poirier, F; Prevost, C; Rimbault, C; Touze, F; Variola, A; Bolzon, B; Brunetti, L; Jeremie, A; Baylac, M; Bourrion, O; De Conto, J M; Gomez, Y; Meot, F; Monseu, N; Tourres, D; Vescovi, C; Chanci, A; Napoly, O; Barber, D P; Bettoni, S; Quatraro, D
2010-01-01
This report details the present status of the Accelerator design for the SuperB Project. It is one of four separate progress reports that, taken collectively, describe progress made on the SuperB Project since the publication of the SuperB Conceptual Design Report in 2007 and the Proceedings of SuperB Workshop VI in Valencia in 2008.
SuperB Progress Report: Detector
Energy Technology Data Exchange (ETDEWEB)
Grauges, E.; /Barcelona U., ECM; Donvito, G.; Spinoso, V.; /INFN, Bari /Bari U.; Manghisoni, M.; Re, V.; Traversi, G.; /INFN, Pavia /Bergamo U., Ingengneria Dept.; Eigen, G.; Fehlker, D.; Helleve, L.; /Bergen U.; Carbone, A.; Di Sipio, R.; Gabrielli, A.; Galli, D.; Giorgi, F.; Marconi, U.; Perazzini, S.; Sbarra, C.; Vagnoni, V.; Valentinetti, S.; Villa, M.; Zoccoli, A.; /INFN, Bologna /Bologna U. /Caltech /Carleton U. /Cincinnati U. /INFN, CNAF /INFN, Ferrara /Ferrara U. /UC, Irvine /Taras Shevchenko U. /Orsay, LAL /LBL, Berkeley /UC, Berkeley /Frascati /INFN, Legnaro /Orsay, IPN /Maryland U. /McGill U. /INFN, Milan /Milan U. /INFN, Naples /Naples U. /Novosibirsk, IYF /INFN, Padua /Padua U. /INFN, Pavia /Pavia U. /INFN, Perugia /Perugia U. /INFN, Perugia /Caltech /INFN, Pisa /Pisa U. /Pisa, Scuola Normale Superiore /PNL, Richland /Queen Mary, U. of London /Rutherford /INFN, Rome /Rome U. /INFN, Rome2 /Rome U.,Tor Vergata /INFN, Rome3 /Rome III U. /SLAC /Tel Aviv U. /INFN, Turin /Turin U. /INFN, Padua /Trento U. /INFN, Trieste /Trieste U. /TRIUMF /British Columbia U. /Montreal U. /Victoria U.
2012-02-14
This report describes the present status of the detector design for SuperB. It is one of four separate progress reports that, taken collectively, describe progress made on the SuperB Project since the publication of the SuperB Conceptual Design Report in 2007 and the Proceedings of SuperB Workshop VI in Valencia in 2008.
2012-01-01
Licence; En 1935, un groupe de mathématiciens français eut l'ambition de reconstruire tout l'édifice mathématique (sans S pour bien montrer l'unité) selon la pensée formaliste de Hilbert. Les membres fondateurs ont été Henri Cartan, Claude Chevalley, Jean Delsarte, Jean Dieudonné, André Weil auxquels se joindra René de Possel. En juillet 1935 fut donc créé, lors d'un séminaire en Auvergne le groupe 'Nicolas Bourbaki'. Le nom de cette association fait référence en fait à une anecdote qui se pa...
What's So Super about Superfoods?
... with meals. The Skinny on Common Super Foods Salmon is a fatty fish that’s low in saturated ... soy nuts are high in polyunsaturated fat, fiber, vitamins and minerals but low in saturated fat. They ...
Super Ministries,Better Administration
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
@@ Chinese lawmakers on March 15th endorsed a State Counci l proposal for institutional overhaul of the tentral government,which involves the establishment of"super ministries"concerning energy,transport,industry and environmental protection.
Directory of Open Access Journals (Sweden)
D. Cane
2013-02-01
Full Text Available In this work, we compare the performance of an hydrological model when driven by probabilistic rain forecast derived from two different post-processing techniques. The region of interest is Piemonte, northwestern Italy, a complex orography area close to the Mediterranean Sea where the forecast are often a challenge for weather models. The May 2008 flood is here used as a case study, and the very dense weather station network allows us for a very good description of the event and initialization of the hydrological model. The ensemble probabilistic forecasts of the rainfall fields are obtained with the Bayesian model averaging, with the classical poor man ensemble approach and with a new technique, the Multimodel SuperEnsemble Dressing. In this case study, the meteo-hydrological chain initialized with the Multimodel SuperEnsemble Dressing is able to provide more valuable discharge ranges with respect to the one initialized with Bayesian model averaging multi-model.
Analysis of mesoscale forecasts using ensemble methods
Gross, Markus
2016-01-01
Mesoscale forecasts are now routinely performed as elements of operational forecasts and their outputs do appear convincing. However, despite their realistic appearance at times the comparison to observations is less favorable. At the grid scale these forecasts often do not compare well with observations. This is partly due to the chaotic system underlying the weather. Another key problem is that it is impossible to evaluate the risk of making decisions based on these forecasts because they do not provide a measure of confidence. Ensembles provide this information in the ensemble spread and quartiles. However, running global ensembles at the meso or sub mesoscale involves substantial computational resources. National centers do run such ensembles, but the subject of this publication is a method which requires significantly less computation. The ensemble enhanced mesoscale system presented here aims not at the creation of an improved mesoscale forecast model. Also it is not to create an improved ensemble syste...
Measuring social interaction in music ensembles.
Volpe, Gualtiero; D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano
2016-05-05
Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances.
Gibbs Ensembles of Nonintersecting Paths
Borodin, Alexei
2008-01-01
We consider a family of determinantal random point processes on the two-dimensional lattice and prove that members of our family can be interpreted as a kind of Gibbs ensembles of nonintersecting paths. Examples include probability measures on lozenge and domino tilings of the plane, some of which are non-translation-invariant. The correlation kernels of our processes can be viewed as extensions of the discrete sine kernel, and we show that the Gibbs property is a consequence of simple linear relations satisfied by these kernels. The processes depend on infinitely many parameters, which are closely related to parametrization of totally positive Toeplitz matrices.
Wind Power Prediction using Ensembles
DEFF Research Database (Denmark)
Giebel, Gregor; Badger, Jake; Landberg, Lars
2005-01-01
offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...
Ensemble Methods Foundations and Algorithms
Zhou, Zhi-Hua
2012-01-01
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity a
Quantum Repeaters and Atomic Ensembles
DEFF Research Database (Denmark)
Borregaard, Johannes
a previous protocol, thereby enabling fast local processing, which greatly enhances the distribution rate. We then move on to describe our work on improving the stability of atomic clocks using entanglement. Entanglement can potentially push the stability of atomic clocks to the so-called Heisenberg limit......, which is the absolute upper limit of the stability allowed by the Heisenberg uncertainty relation. It has, however, been unclear whether entangled state’s enhanced sensitivity to noise would prevent reaching this limit. We have developed an adaptive measurement protocol, which circumvents this problem...... based on atomic ensembles....
A Localized Ensemble Kalman Smoother
Butala, Mark D.
2012-01-01
Numerous geophysical inverse problems prove difficult because the available measurements are indirectly related to the underlying unknown dynamic state and the physics governing the system may involve imperfect models or unobserved parameters. Data assimilation addresses these difficulties by combining the measurements and physical knowledge. The main challenge in such problems usually involves their high dimensionality and the standard statistical methods prove computationally intractable. This paper develops and addresses the theoretical convergence of a new high-dimensional Monte-Carlo approach called the localized ensemble Kalman smoother.
Pott, Sebastian; Lieb, Jason D
2015-01-01
The term 'super-enhancer' has been used to describe groups of putative enhancers in close genomic proximity with unusually high levels of Mediator binding, as measured by chromatin immunoprecipitation and sequencing (ChIP-seq). Here we review the identification and composition of super-enhancers, describe links between super-enhancers, gene regulation and disease, and discuss the functional significance of enhancer clustering. We also provide our perspective regarding the proposition that super-enhancers are a regulatory entity conceptually distinct from what was known before the introduction of the term. Our opinion is that there is not yet strong evidence that super-enhancers are a novel paradigm in gene regulation and that use of the term in this context is not currently justified. However, the term likely identifies strong enhancers that exhibit behaviors consistent with previous models and concepts of transcriptional regulation. In this respect, the super-enhancer definition is useful in identifying regulatory elements likely to control genes important for cell type specification.
Heterogeneous versus Homogeneous Machine Learning Ensembles
Directory of Open Access Journals (Sweden)
Petrakova Aleksandra
2015-12-01
Full Text Available The research demonstrates efficiency of the heterogeneous model ensemble application for a cancer diagnostic procedure. Machine learning methods used for the ensemble model training are neural networks, random forest, support vector machine and offspring selection genetic algorithm. Training of models and the ensemble design is performed by means of HeuristicLab software. The data used in the research have been provided by the General Hospital of Linz, Austria.
Interpreting Tree Ensembles with inTrees
Deng, Houtao
2014-01-01
Tree ensembles such as random forests and boosted trees are accurate but difficult to understand, debug and deploy. In this work, we provide the inTrees (interpretable trees) framework that extracts, measures, prunes and selects rules from a tree ensemble, and calculates frequent variable interactions. An rule-based learner, referred to as the simplified tree ensemble learner (STEL), can also be formed and used for future prediction. The inTrees framework can applied to both classification an...
Holography based super resolution
Hussain, Anwar; Mudassar, Asloob A.
2012-05-01
This paper describes the simulation of a simple technique of superresolution based on holographic imaging in spectral domain. The input beam assembly containing 25 optical fibers with different orientations and positions is placed to illuminate the object in the 4f optical system. The position and orientation of each fiber is calculated with respect to the central fiber in the array. The positions and orientations of the fibers are related to the shift of object spectrum at aperture plane. During the imaging process each fiber is operated once in the whole procedure to illuminate the input object transparency which gives shift to the object spectrum in the spectral domain. This shift of the spectrum is equal to the integral multiple of the pass band aperture width. During the operation of single fiber (ON-state) all other fibers are in OFF-state at that time. The hologram recorded by each fiber at the CCD plane is stored in computer memory. At the end of illumination process total 25 holograms are recorded by the whole fiber array and by applying some post processing and specific algorithm single super resolved image is obtained. The superresolved image is five times better than the band-limited image. The work is demonstrated using computer simulation only.
Analysis of peeling decoder for MET ensembles
Hinton, Ryan
2009-01-01
The peeling decoder introduced by Luby, et al. allows analysis of LDPC decoding for the binary erasure channel (BEC). For irregular ensembles, they analyze the decoder state as a Markov process and present a solution to the differential equations describing the process mean. Multi-edge type (MET) ensembles allow greater precision through specifying graph connectivity. We generalize the the peeling decoder for MET ensembles and derive analogous differential equations. We offer a new change of variables and solution to the node fraction evolutions in the general (MET) case. This result is preparatory to investigating finite-length ensemble behavior.
Hierarchical Bayes Ensemble Kalman Filtering
Tsyrulnikov, Michael
2015-01-01
Ensemble Kalman filtering (EnKF), when applied to high-dimensional systems, suffers from an inevitably small affordable ensemble size, which results in poor estimates of the background error covariance matrix ${\\bf B}$. The common remedy is a kind of regularization, usually an ad-hoc spatial covariance localization (tapering) combined with artificial covariance inflation. Instead of using an ad-hoc regularization, we adopt the idea by Myrseth and Omre (2010) and explicitly admit that the ${\\bf B}$ matrix is unknown and random and estimate it along with the state (${\\bf x}$) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components ${\\bf P}$ and ${\\bf Q}$ of the ${\\bf B}$ matrix into the extended control vector $({\\bf x},{\\bf P},{\\bf Q})$. Similarly, we break the traditional backgrou...
Visualizing ensembles in structural biology.
Melvin, Ryan L; Salsbury, Freddie R
2016-06-01
Displaying a single representative conformation of a biopolymer rather than an ensemble of states mistakenly conveys a static nature rather than the actual dynamic personality of biopolymers. However, there are few apparent options due to the fixed nature of print media. Here we suggest a standardized methodology for visually indicating the distribution width, standard deviation and uncertainty of ensembles of states with little loss of the visual simplicity of displaying a single representative conformation. Of particular note is that the visualization method employed clearly distinguishes between isotropic and anisotropic motion of polymer subunits. We also apply this method to ligand binding, suggesting a way to indicate the expected error in many high throughput docking programs when visualizing the structural spread of the output. We provide several examples in the context of nucleic acids and proteins with particular insights gained via this method. Such examples include investigating a therapeutic polymer of FdUMP (5-fluoro-2-deoxyuridine-5-O-monophosphate) - a topoisomerase-1 (Top1), apoptosis-inducing poison - and nucleotide-binding proteins responsible for ATP hydrolysis from Bacillus subtilis. We also discuss how these methods can be extended to any macromolecular data set with an underlying distribution, including experimental data such as NMR structures.
Interfacing broadband photonic qubits to on-chip cavity-protected rare-earth ensembles
Zhong, Tian; Kindem, Jonathan M.; Rochman, Jake; Faraon, Andrei
2017-01-01
Ensembles of solid-state optical emitters enable broadband quantum storage and transduction of photonic qubits, with applications in high-rate quantum networks for secure communications and interconnecting future quantum computers. To transfer quantum states using ensembles, rephasing techniques are used to mitigate fast decoherence resulting from inhomogeneous broadening, but these techniques generally limit the bandwidth, efficiency and active times of the quantum interface. Here, we use a dense ensemble of neodymium rare-earth ions strongly coupled to a nanophotonic resonator to demonstrate a significant cavity protection effect at the single-photon level--a technique to suppress ensemble decoherence due to inhomogeneous broadening. The protected Rabi oscillations between the cavity field and the atomic super-radiant state enable ultra-fast transfer of photonic frequency qubits to the ions (~50 GHz bandwidth) followed by retrieval with 98.7% fidelity. With the prospect of coupling to other long-lived rare-earth spin states, this technique opens the possibilities for broadband, always-ready quantum memories and fast optical-to-microwave transducers.
China summer precipitation simulations using an optimal ensemble of cumulus schemes
Institute of Scientific and Technical Information of China (English)
Shuyan LIU; Wei GAO; Min XU; Xueyuan WANG; Xin-Zhong LIANG
2009-01-01
RegCM3 (REGional Climate Model) simulations of precipitation in China in 1991 and 1998 are very sensitive to the cumulus parameterization. Among the four schemes available, none has superior skills over the whole of China, but each captures certain observed signals in distinct regions. The Grell scheme with the FritschChappell closure produces the smallest biases over the North; the Grell scheme with the Arakawa-Schubert closure performs the best over the southeast of 100°E;the Anthes-Kuo scheme is superior over the northeast; and the Emanuel scheme is more realistic over the southwest of 100~E and along the Yangtze River Basin. These differences indicate a strong degree of independence and complementarity between the parameterizations. As such,an ensemble is developed from the four schemes, whose relative contributions or weights are optimized locally to yield overall minimum root-mean-square errors from observed daily precipitation. The skill gain is evaluated by applying the identical distribution of the weights in a different period. It is shown that the ensemble always produces gross biases that are smaller than the individual schemes in both 1991 and 1998. The ensemble, however,cannot eliminate the large rainfall deficits over the southwest of 100°E and along the Yangtze River Basin that are systematic across all schemes. Further improvements can be made by a super-ensemble based on more cumulus schemes and/or multiple models.
Electrically tuned super-capacitors
Chowdhury, Tazima S
2015-01-01
Fast charging and discharging of large amounts of electrical energy make super-capacitors ideal for short-term energy storage [1-5]. In its simplest form, the super-capacitor is an electrolytic capacitor made of an anode and a cathode immersed in an electrolyte. As for an ordinary capacitor, minimizing the charge separation distance and increasing the electrode area increase capacitance. In super-capacitors, charge separation is of nano-meter scale at each of the electrode interface (the Helmholtz double layer). Making the electrodes porous increases their effective surface area [6-8]. A separating layer between the anode and the cathode electrodes is used to minimize unintentional electrical discharge (Figure 1). Here we show how to increase the capacitance of super-capacitors by more than 45 percent when modifying the otherwise passive separator layer into an active diode-like structure. Active control of super-capacitors may increase their efficiency during charge and discharge cycles. Controlling ion flow...
Quantization of super Teichmueller spaces
Energy Technology Data Exchange (ETDEWEB)
Aghaei, Nezhla
2016-08-15
The quantization of the Teichmueller spaces of Riemann surfaces has found important applications to conformal field theory and N=2 supersymmetric gauge theories. We construct a quantization of the Teichmueller spaces of super Riemann surfaces, using coordinates associated to the ideal triangulations of super Riemann surfaces. A new feature is the non-trivial dependence on the choice of a spin structure which can be encoded combinatorially in a certain refinement of the ideal triangulation. We construct a projective unitary representation of the groupoid of changes of refined ideal triangulations. Therefore, we demonstrate that the dependence of the resulting quantum theory on the choice of a triangulation is inessential. In the quantum Teichmueller theory, it was observed that the key object defining the Teichmueller theory has a close relation to the representation theory of the Borel half of U{sub q}(sl(2)). In our research we observed that the role of U{sub q}(sl(2)) is taken by quantum superalgebra U{sub q}(osp(1 vertical stroke 2)). A Borel half of U{sub q}(osp(1 vertical stroke 2)) is the super quantum plane. The canonical element of the Heisenberg double of the quantum super plane is evaluated in certain infinite dimensional representations on L{sup 2}(R) x C{sup 1} {sup vertical} {sup stroke} {sup 1} and compared to the flip operator from the Teichmueller theory of super Riemann surfaces.
Improved customer choice predictions using ensemble methods
M.C. van Wezel (Michiel); R. Potharst (Rob)
2005-01-01
textabstractIn this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to
Layered Ensemble Architecture for Time Series Forecasting.
Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin
2016-01-01
Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.
Ensemble methods for handwritten digit recognition
DEFF Research Database (Denmark)
Hansen, Lars Kai; Liisberg, Christian; Salamon, P.
1992-01-01
. It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...
Nonextensivity in magnetic nanoparticle ensembles
Binek, Ch.; Polisetty, S.; He, Xi; Mukherjee, T.; Rajesh, R.; Redepenning, J.
2006-08-01
A superconducting quantum interference device and Faraday rotation technique are used to study dipolar interacting nanoparticles embedded in a polystyrene matrix. Magnetization isotherms are measured for three cylindrically shaped samples of constant diameter but various heights. Detailed analysis of the isotherms supports Tsallis’ conjecture of a magnetic equation of state that involves temperature and magnetic field variables scaled by the logarithm of the number of magnetic nanoparticles. This unusual scaling of thermodynamic variables, which are conventionally considered to be intensive, originates from the nonextensivity of the Gibbs free energy in three-dimensional dipolar interacting particle ensembles. Our experimental evidence for nonextensivity is based on the data collapse of various isotherms that require scaling of the field variable in accordance with Tsallis’ equation of state.
Perception of ensemble statistics requires attention.
Jackson-Nielsen, Molly; Cohen, Michael A; Pitts, Michael A
2017-02-01
To overcome inherent limitations in perceptual bandwidth, many aspects of the visual world are represented as summary statistics (e.g., average size, orientation, or density of objects). Here, we investigated the relationship between summary (ensemble) statistics and visual attention. Recently, it was claimed that one ensemble statistic in particular, color diversity, can be perceived without focal attention. However, a broader debate exists over the attentional requirements of conscious perception, and it is possible that some form of attention is necessary for ensemble perception. To test this idea, we employed a modified inattentional blindness paradigm and found that multiple types of summary statistics (color and size) often go unnoticed without attention. In addition, we found attentional costs in dual-task situations, further implicating a role for attention in statistical perception. Overall, we conclude that while visual ensembles may be processed efficiently, some amount of attention is necessary for conscious perception of ensemble statistics.
Popular Ensemble Methods: An Empirical Study
Maclin, R; 10.1613/jair.614
2011-01-01
An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any of the single classifiers in the ensemble. Bagging (Breiman, 1996c) and Boosting (Freund and Shapire, 1996; Shapire, 1990) are two relatively new but popular methods for producing ensembles. In this paper we evaluate these methods on 23 data sets using both neural networks and decision trees as our classification algorithm. Our results clearly indicate a number of conclusions. First, while Bagging is almost always more accurate than a single classifier, it is sometimes much less accurate than Boosting. On the other hand, Boosting can create ensembles that are less accurate than a single classifier -- especially when using neural networks. Analysis indicates that the performance of the Boosting methods is dependent on the characteristics of the data set being exa...
Super-Virasoro anomaly, super-Weyl anomaly and the super-Liouville action for 2D supergravity
Fujiwara, T; Suzuki, T; Fujiwara, Takanori; Igarashi, Hiroshi; Suzuki, Tadao
1996-01-01
The relation between super-Virasoro anomaly and super-Weyl anomaly in N=1 NSR superstring coupled with 2D supergravity is investigated from canonical theoretical view point. The WZW action canceling the super-Virasoro anomaly is explicitly constructed. It is super-Weyl invariant but nonlocal functional of 2D supergravity. The nonlocality can be remedied by the super-Liouvlle action, which in turn recovers the super-Weyl anomaly. The final gravitational effective action turns out to be local but noncovariant super-Liouville action, describing the dynamical behavior of the super-Liouville fields. The BRST invariance of this approach is examined in the superconformal gauge and in the light-cone gauge.
Bouallegue, Zied Ben; Theis, Susanne E; Pinson, Pierre
2015-01-01
Probabilistic forecasts in the form of ensemble of scenarios are required for complex decision making processes. Ensemble forecasting systems provide such products but the spatio-temporal structures of the forecast uncertainty is lost when statistical calibration of the ensemble forecasts is applied for each lead time and location independently. Non-parametric approaches allow the reconstruction of spatio-temporal joint probability distributions at a low computational cost.For example, the ensemble copula coupling (ECC) method consists in rebuilding the multivariate aspect of the forecast from the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error. The new approach which preserves the dynamical development of the ensemble members is called dynamic ensemble copula coupling (...
The Super-Kamiokande Experiment
Walter, C W
2008-01-01
Super-Kamiokande is a 50 kiloton water Cherenkov detector located at the Kamioka Observatory of the Institute for Cosmic Ray Research, University of Tokyo. It was designed to study neutrino oscillations and carry out searches for the decay of the nucleon. The Super-Kamiokande experiment began in 1996 and in the ensuing decade of running has produced extremely important results in the fields of atmospheric and solar neutrino oscillations, along with setting stringent limits on the decay of the nucleon and the existence of dark matter and astrophysical sources of neutrinos. Perhaps most crucially, Super-Kamiokande for the first time definitively showed that neutrinos have mass and undergo flavor oscillations. This chapter will summarize the published scientific output of the experiment with a particular emphasis on the atmospheric neutrino results.
Super-resolution microscopy of single atoms in optical lattices
Alberti, Andrea; Alt, Wolfgang; Brakhane, Stefan; Karski, Michał; Reimann, René; Widera, Artur; Meschede, Dieter
2015-01-01
We report on image processing techniques and experimental procedures to determine the lattice-site positions of single atoms in an optical lattice with high reliability, even for limited acquisition time or optical resolution. Determining the positions of atoms beyond the diffraction limit relies on parametric deconvolution in close analogy to methods employed in super-resolution microscopy. We develop a deconvolution method that makes effective use of the prior knowledge of the optical transfer function, noise properties, and discreteness of the optical lattice. We show that accurate knowledge of the image formation process enables a dramatic improvement on the localization reliability. This is especially relevant for closely packed ensembles of atoms where the separation between particles cannot be directly optically resolved. Furthermore, we demonstrate experimental methods to precisely reconstruct the point spread function with sub-pixel resolution from fluorescence images of single atoms, and we give a m...
Microsphere Super-resolution Imaging
Wang, Zengbo
2015-01-01
Recently, it was discovered that microsphere can generate super-resolution focusing beyond diffraction limit. This has led to the development of an exciting super-resolution imaging technique -microsphere nanoscopy- that features a record resolution of 50 nm under white lights. Different samples have been directly imaged in high resolution and real time without labelling, including both non-biological (nano devices, structures and materials) and biological (subcellular details, viruses) samples. This chapter reviews the technique, which covers its background, fundamentals, experiments, mechanisms as well as the future outlook.
Interactive Super Mario Bros Evolution
DEFF Research Database (Denmark)
Sørensen, Patrikk D.; Olsen, Jeppeh M.; Risi, Sebastian
2016-01-01
to encourage the evolution of desired behaviors. In this paper, we show how casual users can create controllers for \\emph{Super Mario Bros} through an interactive evolutionary computation (IEC) approach, without prior domain or programming knowledge. By iteratively selecting Super Mario behaviors from a set...... of candidates, users are able to guide evolution towards a variety of different behaviors, which would be difficult with an automated approach. Additionally, the user-evolved controllers perform similarly well as controllers evolved with a traditional fitness-based approach when comparing distance traveled...
Quantisation of super Teichmueller theory
Energy Technology Data Exchange (ETDEWEB)
Aghaei, Nezhla [DESY Hamburg (Germany). Theory Group; Hamburg Univ. (Germany). Dept. of Mathematics; Pawelkiewicz, Michal; Techner, Joerg [DESY Hamburg (Germany). Theory Group
2015-12-15
We construct a quantisation of the Teichmueller spaces of super Riemann surfaces using coordinates associated to ideal triangulations of super Riemann surfaces. A new feature is the non-trivial dependence on the choice of a spin structure which can be encoded combinatorially in a certain refinement of the ideal triangulation. By constructing a projective unitary representation of the groupoid of changes of refined ideal triangulations we demonstrate that the dependence of the resulting quantum theory on the choice of a triangulation is inessential.
Quantisation of super Teichmueller theory
Aghaei, Nezhla; Teschner, Joerg
2015-01-01
We construct a quantisation of the Teichmueller spaces of super Riemann surfaces using coordinates associated to ideal triangulations of super Riemann surfaces. A new feature is the non-trivial dependence on the choice of a spin structure which can be encoded combinatorially in a certain refinement of the ideal triangulation. By constructing a projective unitary representation of the groupoid of changes of refined ideal triangulations we demonstrate that the dependence of the resulting quantum theory on the choice of a triangulation is inessential.
The construction of orthodox super rpp semigroups
Institute of Scientific and Technical Information of China (English)
HE Yong; GUO Yuqi; Kar Ping Shum
2004-01-01
We define orthodox super rpp semigroups and study their semilattice decompositions. Standard representation theorem of orthodox super rpp semigroups whose subband of idempotents is in the varieties of bands described by an identity with at most three variables are obtained.
Calculations of canonical averages from the grand canonical ensemble.
Kosov, D S; Gelin, M F; Vdovin, A I
2008-02-01
Grand canonical and canonical ensembles become equivalent in the thermodynamic limit, but when the system size is finite the results obtained in the two ensembles deviate from each other. In many important cases, the canonical ensemble provides an appropriate physical description but it is often much easier to perform the calculations in the corresponding grand canonical ensemble. We present a method to compute averages in the canonical ensemble based on calculations of the expectation values in the grand canonical ensemble. The number of particles, which is fixed in the canonical ensemble, is not necessarily the same as the average number of particles in the grand canonical ensemble.
Hybrid Data Assimilation without Ensemble Filtering
Todling, Ricardo; Akkraoui, Amal El
2014-01-01
The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.
MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging
Chen, Lei; Kamel, Mohamed S.
2016-01-01
In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.
Super-resolution Phase Tomography
Depeursinge, Christian
2013-04-21
Digital Holographic Microscopy (DHM) yields reconstructed complex wavefields. It allows synthesizing the aperture of a virtual microscope up to 2π, offering super-resolution phase images. Live images of micro-organisms and neurons with resolution less than 100 nm are presented.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
@@I. Demand for super high yield rice in China Rice is one of the main staple food in China. The performance of rice sector in production and yield had been very impressive in the last four decades. However, rice production and yield has stagnated since 1990.
Super Girls Still Center Stage
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
The TV singing contest continues to draw a devoted audience, but will its impact on Chinese culture fall away like a shooting star? Ask any teenage girl in China to name the finalists of last year's Super Girl show and chances are she will instantly come up with the three big names.She'll probable
Analysis of Forensic Super Timelines
2012-06-14
BIB .1 vii List of Figures Figure Page...Hacker disconnects from User’s system User clicks off Screen Saver User closes Solitaire program User logs off system BIB .1...analysis- tapestry_33836. BIB .2 Guðjónsson, K. (2010). Mastering the super timeline with log2timeline. SANS Gold Paper accepted June 29,2010
4DVAR by ensemble Kalman smoother
Mandel, Jan; Gratton, Serge
2013-01-01
We propose to use the ensemble Kalman smoother (EnKS) as linear least squares solver in the Gauss-Newton method for the large nonlinear least squares in incremental 4DVAR. The ensemble approach is naturally parallel over the ensemble members and no tangent or adjoint operators are needed. Further, adding a regularization term results in replacing the Gauss-Newton method, which may diverge, by^M the Levenberg-Marquardt method, which is known to be convergent. The regularization is implemented efficiently as an additional observation in the EnKS.
Derivation of Mayer Series from Canonical Ensemble
Wang, Xian-Zhi
2016-02-01
Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.
Super-resolution microscopy of single atoms in optical lattices
Alberti, Andrea; Robens, Carsten; Alt, Wolfgang; Brakhane, Stefan; Karski, Michał; Reimann, René; Widera, Artur; Meschede, Dieter
2016-05-01
We report on image processing techniques and experimental procedures to determine the lattice-site positions of single atoms in an optical lattice with high reliability, even for limited acquisition time or optical resolution. Determining the positions of atoms beyond the diffraction limit relies on parametric deconvolution in close analogy to methods employed in super-resolution microscopy. We develop a deconvolution method that makes effective use of the prior knowledge of the optical transfer function, noise properties, and discreteness of the optical lattice. We show that accurate knowledge of the image formation process enables a dramatic improvement on the localization reliability. This allows us to demonstrate super-resolution of the atoms’ position in closely packed ensembles where the separation between particles cannot be directly optically resolved. Furthermore, we demonstrate experimental methods to precisely reconstruct the point spread function with sub-pixel resolution from fluorescence images of single atoms, and we give a mathematical foundation thereof. We also discuss discretized image sampling in pixel detectors and provide a quantitative model of noise sources in electron multiplying CCD cameras. The techniques developed here are not only beneficial to neutral atom experiments, but could also be employed to improve the localization precision of trapped ions for ultra precise force sensing.
Nonextensivity in Magnetic Nanocluster Ensembles
Binek, Christian; Polisetty, Srinivas; He, Xi; Mukherjee, Tathagata; Rajasekeran, Rajesh; Redepenning, Jody
2006-03-01
We study the scaling behavior of dipolar interacting nanoparticles in 3D samples of various sizes but constant particle density. Ferromagnetic γ-Fe2O3 clusters embedded in a polystyrene matrix are fabricated by thermal decomposition of metal carbonyls. Transmission electron microscopy reveals a narrow size distribution of 12 nm clusters. They are randomly dispersed in the matrix with an average separation of 80 nm. Magnetization isotherms of these single domain particle ensembles are measured by SQUID magnetometry above the blocking temperature TB =115K where non-equilibrium effects are avoided. After demagnetization corrections which convert the applied magnetic fields into internal fields, H, a data collapse is achieved when scaling the magnetic moment, m, and H by appropriate factors. The latter are theoretically predicted functions of the number of particles and determined here numerically. Scaling of H takes into account the nonextensive (NE) behavior of dipolar interacting particles. In the case of long range interactions a scaling schema has been proposed by Tsallis and confirmed by simulations. The controversial field of NE thermodynamics requires however experimental evidence provided here.
Ensemble Dynamics and Bred Vectors
Balci, Nusret; Restrepo, Juan M; Sell, George R
2011-01-01
We introduce the new concept of an EBV to assess the sensitivity of model outputs to changes in initial conditions for weather forecasting. The new algorithm, which we call the "Ensemble Bred Vector" or EBV, is based on collective dynamics in essential ways. By construction, the EBV algorithm produces one or more dominant vectors. We investigate the performance of EBV, comparing it to the BV algorithm as well as the finite-time Lyapunov Vectors. We give a theoretical justification to the observed fact that the vectors produced by BV, EBV, and the finite-time Lyapunov vectors are similar for small amplitudes. Numerical comparisons of BV and EBV for the 3-equation Lorenz model and for a forced, dissipative partial differential equation of Cahn-Hilliard type that arises in modeling the thermohaline circulation, demonstrate that the EBV yields a size-ordered description of the perturbation field, and is more robust than the BV in the higher nonlinear regime. The EBV yields insight into the fractal structure of th...
Ensemble Forecasting of Tropical Cyclone Motion Using a Baroclinic Model
Institute of Scientific and Technical Information of China (English)
Xiaqiong ZHOU; Johnny C.L.CHEN
2006-01-01
The purpose of this study is to investigate the effectiveness of two different ensemble forecasting (EF) techniques-the lagged-averaged forecast (LAF) and the breeding of growing modes (BGM). In the BGM experiments, the vortex and the environment are perturbed separately (named BGMV and BGME).Tropical cyclone (TC) motions in two difficult situations are studied: a large vortex interacting with its environment, and an apparent binary interaction. The former is Typhoon Yancy and the latter involves Typhoon Ed and super Typhoon Flo, all occurring during the Tropical Cyclone Motion Experiment TCM-90. The model used is the baroclinic model of the University of New South Wales. The lateral boundary tendencies are computed from atmospheric analysis data. Only the relative skill of the ensemble forecast mean over the control run is used to evaluate the effectiveness of the EF methods, although the EF technique is also used to quantify forecast uncertainty in some studies. In the case of Yancy, the ensemble mean forecasts of each of the three methodologies are better than that of the control, with LAF being the best. The mean track of the LAF is close to the best track, and it predicts landfall over Taiwan. The improvements in LAF and the full BGM where both the environment and vortex are perturbed suggest the importance of combining the perturbation of the vortex and environment when the interaction between the two is appreciable. In the binary interaction case of Ed and Flo, the forecasts of Ed appear to be insensitive to perturbations of the environment and/or the vortex, which apparently results from erroneous forecasts by the model of the interaction between the subtropical ridge and Ed, as well as from the interaction between the two typhoons, thus reducing the effectiveness of the EF technique. This conclusion is reached through sensitivity experiments on the domain of the model and by adding or eliminating certain features in the model atmosphere. Nevertheless, the
A 4D-Ensemble-Variational System for Data Assimilation and Ensemble Initialization
Bowler, Neill; Clayton, Adam; Jardak, Mohamed; Lee, Eunjoo; Jermey, Peter; Lorenc, Andrew; Piccolo, Chiara; Pring, Stephen; Wlasak, Marek; Barker, Dale; Inverarity, Gordon; Swinbank, Richard
2016-04-01
The Met Office has been developing a four-dimensional ensemble variational (4DEnVar) data assimilation system over the past four years. The 4DEnVar system is intended both as data assimilation system in its own right and also an improved means of initializing the Met Office Global and Regional Ensemble Prediction System (MOGREPS). The global MOGREPS ensemble has been initialized by running an ensemble of 4DEnVars (En-4DEnVar). The scalability and maintainability of ensemble data assimilation methods make them increasingly attractive, and 4DEnVar may be adopted in the context of the Met Office's LFRic project to redevelop the technical infrastructure to enable its Unified Model (MetUM) to be run efficiently on massively parallel supercomputers. This presentation will report on the results of the 4DEnVar development project, including experiments that have been run using ensemble sizes of up to 200 members.
Transition from Poisson to circular unitary ensemble
Indian Academy of Sciences (India)
Vinayak; Akhilesh Pandey
2009-09-01
Transitions to universality classes of random matrix ensembles have been useful in the study of weakly-broken symmetries in quantum chaotic systems. Transitions involving Poisson as the initial ensemble have been particularly interesting. The exact two-point correlation function was derived by one of the present authors for the Poisson to circular unitary ensemble (CUE) transition with uniform initial density. This is given in terms of a rescaled symmetry breaking parameter Λ. The same result was obtained for Poisson to Gaussian unitary ensemble (GUE) transition by Kunz and Shapiro, using the contour-integral method of Brezin and Hikami. We show that their method is applicable to Poisson to CUE transition with arbitrary initial density. Their method is also applicable to the more general ℓ CUE to CUE transition where CUE refers to the superposition of ℓ independent CUE spectra in arbitrary ratio.
Ensemble treatments of thermal pairing in nuclei
Hung, Nguyen Quang; Dang, Nguyen Dinh
2009-10-01
A systematic comparison is conducted for pairing properties of finite systems at nonzero temperature as predicted by the exact solutions of the pairing problem embedded in three principal statistical ensembles, namely the grandcanonical ensemble, canonical ensemble and microcanonical ensemble, as well as the unprojected (FTBCS1+SCQRPA) and Lipkin-Nogami projected (FTLN1+SCQRPA) theories that include the quasiparticle number fluctuation and coupling to pair vibrations within the self-consistent quasiparticle random-phase approximation. The numerical calculations are performed for the pairing gap, total energy, heat capacity, entropy, and microcanonical temperature within the doubly-folded equidistant multilevel pairing model. The FTLN1+SCQRPA predictions are found to agree best with the exact grand-canonical results. In general, all approaches clearly show that the superfluid-normal phase transition is smoothed out in finite systems. A novel formula is suggested for extracting the empirical pairing gap in reasonable agreement with the exact canonical results.
Ensemble Machine Learning Methods and Applications
Ma, Yunqian
2012-01-01
It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...
Ensemble Learning for Free with Evolutionary Algorithms ?
Gagné, Christian; Schoenauer, Marc; Tomassini, Marco
2007-01-01
Evolutionary Learning proceeds by evolving a population of classifiers, from which it generally returns (with some notable exceptions) the single best-of-run classifier as final result. In the meanwhile, Ensemble Learning, one of the most efficient approaches in supervised Machine Learning for the last decade, proceeds by building a population of diverse classifiers. Ensemble Learning with Evolutionary Computation thus receives increasing attention. The Evolutionary Ensemble Learning (EEL) approach presented in this paper features two contributions. First, a new fitness function, inspired by co-evolution and enforcing the classifier diversity, is presented. Further, a new selection criterion based on the classification margin is proposed. This criterion is used to extract the classifier ensemble from the final population only (Off-line) or incrementally along evolution (On-line). Experiments on a set of benchmark problems show that Off-line outperforms single-hypothesis evolutionary learning and state-of-art ...
Reversible Projective Measurement in Quantum Ensembles
Khitrin, Anatoly; Lee, Jae-Seung
2010-01-01
We present experimental NMR demonstration of a scheme of reversible projective measurement, which allows extracting information on outcomes and probabilities of a projective measurement in a non-destructive way, with a minimal net effect on the quantum state of an ensemble. The scheme uses reversible dynamics and weak measurement of the intermediate state. The experimental system is an ensemble of 133Cs (S = 7/2) nuclei in a liquid-crystalline matrix.
Ozone ensemble forecast with machine learning algorithms
Mallet, Vivien; Stoltz, Gilles; Mauricette, Boris
2009-01-01
International audience; We apply machine learning algorithms to perform sequential aggregation of ozone forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system Polyphemus. The ensemble simulations are obtained by changes in the physical parameterizations, the numerical schemes, and the input data to the models. The simulations are carried out for summer 2001 over western Europe in order to forecast ozone daily peaks and ozone hourly concentrati...
Cluster Ensemble-based Image Segmentation
Xiaoru Wang; Junping Du; Shuzhe Wu; Xu Li; Fu Li
2013-01-01
Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories ...
Calibrating ensemble reliability whilst preserving spatial structure
Directory of Open Access Journals (Sweden)
Jonathan Flowerdew
2014-03-01
Full Text Available Ensemble forecasts aim to improve decision-making by predicting a set of possible outcomes. Ideally, these would provide probabilities which are both sharp and reliable. In practice, the models, data assimilation and ensemble perturbation systems are all imperfect, leading to deficiencies in the predicted probabilities. This paper presents an ensemble post-processing scheme which directly targets local reliability, calibrating both climatology and ensemble dispersion in one coherent operation. It makes minimal assumptions about the underlying statistical distributions, aiming to extract as much information as possible from the original dynamic forecasts and support statistically awkward variables such as precipitation. The output is a set of ensemble members preserving the spatial, temporal and inter-variable structure from the raw forecasts, which should be beneficial to downstream applications such as hydrological models. The calibration is tested on three leading 15-d ensemble systems, and their aggregation into a simple multimodel ensemble. Results are presented for 12 h, 1° scale over Europe for a range of surface variables, including precipitation. The scheme is very effective at removing unreliability from the raw forecasts, whilst generally preserving or improving statistical resolution. In most cases, these benefits extend to the rarest events at each location within the 2-yr verification period. The reliability and resolution are generally equivalent or superior to those achieved using a Local Quantile-Quantile Transform, an established calibration method which generalises bias correction. The value of preserving spatial structure is demonstrated by the fact that 3×3 averages derived from grid-scale precipitation calibration perform almost as well as direct calibration at 3×3 scale, and much better than a similar test neglecting the spatial relationships. Some remaining issues are discussed regarding the finite size of the output
Liu, Li; Xu, Yue-Ping
2017-04-01
Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.
Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique
Directory of Open Access Journals (Sweden)
Jan D. Keller
2008-12-01
Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.
Super-translations and super-rotations at the horizon
Donnay, Laura; Gonzalez, Hernan A; Pino, Miguel
2015-01-01
We show that the asymptotic symmetries close to non-extremal black hole horizons are generated by an extension of super-translations. This group is generated by a semi-direct sum of Virasoro and abelian currents. The charges associated to the asymptotic Killing symmetries satisfy the same algebra. When considering the special case of the stationary black hole, the zero mode charges correspond to the angular momentum and the entropy at the horizon.
Minimal redefinition of the OSV ensemble
Parvizi, S; Parvizi, Shahrokh; Tavanfar, Alireza
2005-01-01
In the interesting conjecture, Z_{BH}=|Z_{top}|^2, proposed by Ooguri, Strominger and Vafa (OSV), the black hole ensemble is a mixed ensemble, and resulting degeneracy of states as obtained from the ensemble inverse-Laplace integration, suffer from prefactors which do not respect the (relevant) electric-magnetic dualities. One idea to overcome this deficiency, as claimed recently, is imposing a nontrivial measure for the ensemble sum. We address this problem and upon a redefinition of the OSV ensemble whose variables are as numerous as the electric potentials, show that for restoring the symmetry no non-Euclidean measure is needful. In detail, we rewrite the OSV free energy as a function of new variables which are combinations of the electric-potentials and the black hole charges. Subsequently the Legendre transformation which bridges between the entropy and the black hole free energy in terms of these variables, points to a generalized ensemble. In this context we will consider all the cases of relevance: sm...
Level density for deformations of the Gaussian orthogonal ensemble
Bertuola, A C; Hussein, M S; Pato, M P; Sargeant, A J
2004-01-01
Formulas are derived for the average level density of deformed, or transition, Gaussian orthogonal random matrix ensembles. After some general considerations about Gaussian ensembles we derive formulas for the average level density for (i) the transition from the Gaussian orthogonal ensemble (GOE) to the Poisson ensemble and (ii) the transition from the GOE to $m$ GOEs.
The classicality and quantumness of a quantum ensemble
Zhu, Xuanmin; Wu, Shengjun; Liu, Quanhui
2010-01-01
In this paper, we investigate the classicality and quantumness of a quantum ensemble. We define a quantity called classicality to characterize how classical a quantum ensemble is. An ensemble of commuting states that can be manipulated classically has a unit classicality, while a general ensemble has a classicality less than 1. We also study how quantum an ensemble is by defining a related quantity called quantumness. We find that the classicality of an ensemble is closely related to how perfectly the ensemble can be cloned, and that the quantumness of an ensemble is essentially responsible for the security of quantum key distribution(QKD) protocols using that ensemble. Furthermore, we show that the quantumness of an ensemble used in a QKD protocol is exactly the attainable lower bound of the error rate in the sifted key.
Ensemble postprocessing for probabilistic quantitative precipitation forecasts
Bentzien, S.; Friederichs, P.
2012-12-01
Precipitation is one of the most difficult weather variables to predict in hydrometeorological applications. In order to assess the uncertainty inherent in deterministic numerical weather prediction (NWP), meteorological services around the globe develop ensemble prediction systems (EPS) based on high-resolution NWP systems. With non-hydrostatic model dynamics and without parameterization of deep moist convection, high-resolution NWP models are able to describe convective processes in more detail and provide more realistic mesoscale structures. However, precipitation forecasts are still affected by displacement errors, systematic biases and fast error growth on small scales. Probabilistic guidance can be achieved from an ensemble setup which accounts for model error and uncertainty of initial and boundary conditions. The German Meteorological Service (Deutscher Wetterdienst, DWD) provides such an ensemble system based on the German-focused limited-area model COSMO-DE. With a horizontal grid-spacing of 2.8 km, COSMO-DE is the convection-permitting high-resolution part of the operational model chain at DWD. The COSMO-DE-EPS consists of 20 realizations of COSMO-DE, driven by initial and boundary conditions derived from 4 global models and 5 perturbations of model physics. Ensemble systems like COSMO-DE-EPS are often limited with respect to ensemble size due to the immense computational costs. As a consequence, they can be biased and exhibit insufficient ensemble spread, and probabilistic forecasts may be not well calibrated. In this study, probabilistic quantitative precipitation forecasts are derived from COSMO-DE-EPS and evaluated at more than 1000 rain gauges located all over Germany. COSMO-DE-EPS is a frequently updated ensemble system, initialized 8 times a day. We use the time-lagged approach to inexpensively increase ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Moreover, we will show that statistical
Institute of Scientific and Technical Information of China (English)
柚子
2011-01-01
近日，英国伦敦Super Design展在伦敦Wakefield大街的The Dairy展厅如期举行。本次展览展出了来自包括知名设计师和新兴设计师的特别定制的工作室作品：到如今已经是第五个年头的伦敦Super Deslgn展，力图强发展，展出形式别出心裁、独树一帜，从一个崭新．活跃的角度集展示当代艺术。
Super-Kamiokande atmospheric neutrinos
Energy Technology Data Exchange (ETDEWEB)
Moriyama, S. [Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Higashi Mozumi, Hida city, Gifu prefecture (Japan)
2005-08-15
Results on atmospheric neutrino analysis at Super-Kamiokande I is presented. The whole data set of atmospheric neutrino sample in Super-Kamiokande I is consistently explained with an assumption of pure {nu}{sub {mu}}-{nu}{sub {tau}} oscillations. The allowed range of parameters is 1.5x10{sup -3}<{delta}m{sup 2}<3.4x10{sup -3} eV{sup 2} and sin{sup 2}2{theta}>0.92 at 90% C.L. In the oscillation analysis, we improved the treatment of systematic errors so that they can be considered as independent. This makes possible to find which systematic errors have larger effect on the analysis results. Some sensitivity studies under several assumptions of improvements in systematic errors are presented.
Institute of Scientific and Technical Information of China (English)
2008-01-01
The world has entered the "super capitalism" era when one third of its economic activities are controlled by less than 3 percent of global financial capital. This year,a global economic recession,triggered by the U.S. subprime mortgage crisis,seems unavoidable. To tackle international financial problems,Tao Dong,Chief Economist for Asia at Credit Suisse First Boston in Hong Kong,shared his insights with China Business Journal. Excerpts follow.
2006-01-01
What happened? A number of accidents have occurred with the use of 'Super Glues'. Some individuals have suffered injuries - severe irritation, or skin bonded together - through getting glue on their face and in their eyes. What are the hazards associated with glues? 'Super Glues' (i.e. cyanoacrylates): Are harmful if swallowed and are chemical irritants to the eyes, respiratory system and skin. Present the risk of polymerization (hardening) leading to skin damage. Be careful ! 'Super Glues' can bond to skin and eyes in seconds. Note: Other glues, resins and hardeners are also chemicals and as such can cause serious damage to the skin, eyes, respiratory or digestive tract. (For example: some components can be toxic, harmful, corrosive, sensitizing agents, etc.). How to prevent accidents in the future? Read the Material Safety Data Sheet (MSDS) for all of the glues you work with. Check the label on the container to find out which of the materials you work with are hazardous. Wear the right Per...
Super-Eccentric Migrating Jupiters
Socrates, Aristotle; Dong, Subo; Tremaine, Scott
2011-01-01
An important class of formation theories for hot Jupiters involves the excitation of extreme orbital eccentricity (e=0.99 or even larger) followed by tidal dissipation at periastron passage that eventually circularizes the planetary orbit at a period less than 10 days. In a steady state, this mechanism requires the existence of a significant population of super-eccentric (e>0.9) migrating Jupiters with long orbital periods and periastron distances of only a few stellar radii. For these super-eccentric planets, the periastron is fixed due to conservation of orbital angular momentum and the energy dissipated per orbit is constant, implying that the rate of change in semi-major axis a is \\dot a \\propto a^0.5 and consequently the number distribution satisfies dN/dlog a\\propto a^0.5. If this formation process produces most hot Jupiters, Kepler should detect several super-eccentric migrating progenitors of hot Jupiters, allowing for a test of high-eccentricity migration scenarios.
SUPER-ECCENTRIC MIGRATING JUPITERS
Energy Technology Data Exchange (ETDEWEB)
Socrates, Aristotle; Katz, Boaz; Dong Subo; Tremaine, Scott [Institute for Advanced Study, Princeton, NJ 08540 (United States)
2012-05-10
An important class of formation theories for hot Jupiters involves the excitation of extreme orbital eccentricity (e = 0.99 or even larger) followed by tidal dissipation at periastron passage that eventually circularizes the planetary orbit at a period less than 10 days. In a steady state, this mechanism requires the existence of a significant population of super-eccentric (e > 0.9) migrating Jupiters with long orbital periods and periastron distances of only a few stellar radii. For these super-eccentric planets, the periastron is fixed due to conservation of orbital angular momentum and the energy dissipated per orbit is constant, implying that the rate of change in semi-major axis a is a-dot {proportional_to}a{sup 1/2} and consequently the number distribution satisfies dN/d log a{proportional_to}a{sup 1/2}. If this formation process produces most hot Jupiters, Kepler should detect several super-eccentric migrating progenitors of hot Jupiters, allowing for a test of high-eccentricity migration scenarios.
Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing
Toye, Habib
2017-05-26
We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.
Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing
Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim
2017-07-01
We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.
DEFF Research Database (Denmark)
Ben Bouallègue, Zied; Heppelmann, Tobias; Theis, Susanne E.
2015-01-01
Probabilistic forecasts in the form of ensemble of scenarios are required for complex decision making processes. Ensemble forecasting systems provide such products but the spatio-temporal structures of the forecast uncertainty is lost when statistical calibration of the ensemble forecasts...... is applied for each lead time and location independently. Non-parametric approaches allow the reconstruction of spatio-temporal joint probability distributions at a low computational cost.For example, the ensemble copula coupling (ECC) method consists in rebuilding the multivariate aspect of the forecast...... from the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error...
DEFF Research Database (Denmark)
Ben Bouallègue, Zied; Heppelmann, Tobias; Theis, Susanne E.
2016-01-01
Probabilistic forecasts in the form of ensemble of scenarios are required for complex decision making processes. Ensemble forecasting systems provide such products but the spatio-temporal structures of the forecast uncertainty is lost when statistical calibration of the ensemble forecasts...... is applied for each lead time and location independently. Non-parametric approaches allow the reconstruction of spatio-temporal joint probability distributions at a low computational cost. For example, the ensemble copula coupling (ECC) method rebuilds the multivariate aspect of the forecast from...... the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error. The new...
Multiscale macromolecular simulation: role of evolving ensembles.
Singharoy, A; Joshi, H; Ortoleva, P J
2012-10-22
Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin time step is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers.
Watching the Birth of Super Star Clusters
Turner, J L; Turner, Jean L.; Beck, Sara C.
2003-01-01
Subarcsecond infrared and radio observations yield important information about the formation of super star clusters from their surrounding gas. We discuss the general properties of ionized and molecular gas near young, forming SSCs, as illustrated by the prototypical young forming super star cluster nebula in the dwarf galaxy, NGC 5253. This super star cluster appears to have a gravitationally bound nebula. The lack of molecular gas suggests a very high star formation efficiency, consistent with the formation of a large, bound star cluster.
Control and Synchronization of Neuron Ensembles
Li, Jr-Shin; Ruths, Justin
2011-01-01
Synchronization of oscillations is a phenomenon prevalent in natural, social, and engineering systems. Controlling synchronization of oscillating systems is motivated by a wide range of applications from neurological treatment of Parkinson's disease to the design of neurocomputers. In this article, we study the control of an ensemble of uncoupled neuron oscillators described by phase models. We examine controllability of such a neuron ensemble for various phase models and, furthermore, study the related optimal control problems. In particular, by employing Pontryagin's maximum principle, we analytically derive optimal controls for spiking single- and two-neuron systems, and analyze the applicability of the latter to an ensemble system. Finally, we present a robust computational method for optimal control of spiking neurons based on pseudospectral approximations. The methodology developed here is universal to the control of general nonlinear phase oscillators.
On large deviations for ensembles of distributions
Khrychev, D. A.
2013-11-01
The paper is concerned with the large deviations problem in the Freidlin-Wentzell formulation without the assumption of the uniqueness of the solution to the equation involving white noise. In other words, it is assumed that for each \\varepsilon>0 the nonempty set \\mathscr P_\\varepsilon of weak solutions is not necessarily a singleton. Analogues of a number of concepts in the theory of large deviations are introduced for the set \\{\\mathscr P_\\varepsilon,\\,\\varepsilon>0\\}, hereafter referred to as an ensemble of distributions. The ensembles of weak solutions of an n-dimensional stochastic Navier-Stokes system and stochastic wave equation with power-law nonlinearity are shown to be uniformly exponentially tight. An idempotent Wiener process in a Hilbert space and idempotent partial differential equations are defined. The accumulation points in the sense of large deviations of the ensembles in question are shown to be weak solutions of the corresponding idempotent equations. Bibliography: 14 titles.
Cavity cooling of an ensemble spin system.
Wood, Christopher J; Borneman, Troy W; Cory, David G
2014-02-07
We describe how sideband cooling techniques may be applied to large spin ensembles in magnetic resonance. Using the Tavis-Cummings model in the presence of a Rabi drive, we solve a Markovian master equation describing the joint spin-cavity dynamics to derive cooling rates as a function of ensemble size. Our calculations indicate that the coupled angular momentum subspaces of a spin ensemble containing roughly 10(11) electron spins may be polarized in a time many orders of magnitude shorter than the typical thermal relaxation time. The described techniques should permit efficient removal of entropy for spin-based quantum information processors and fast polarization of spin samples. The proposed application of a standard technique in quantum optics to magnetic resonance also serves to reinforce the connection between the two fields, which has recently begun to be explored in further detail due to the development of hybrid designs for manufacturing noise-resilient quantum devices.
Characteristic polynomials in real Ginibre ensembles
Energy Technology Data Exchange (ETDEWEB)
Akemann, G; Phillips, M J [Department of Mathematical Sciences and BURSt Research Centre, Brunel University West London, UB8 3PH Uxbridge (United Kingdom); Sommers, H-J [Fachbereich Physik, Universitaet Duisburg-Essen, 47048 Duisburg (Germany)], E-mail: Gernot.Akemann@brunel.ac.uk, E-mail: Michael.Phillips@brunel.ac.uk, E-mail: H.J.Sommers@uni-due.de
2009-01-09
We calculate the average of two characteristic polynomials for the real Ginibre ensemble of asymmetric random matrices, and its chiral counterpart. Considered as quadratic forms they determine a skew-symmetric kernel from which all complex eigenvalue correlations can be derived. Our results are obtained in a very simple fashion without going to an eigenvalue representation, and are completely new in the chiral case. They hold for Gaussian ensembles which are partly symmetric, with kernels given in terms of Hermite and Laguerre polynomials respectively, depending on an asymmetry parameter. This allows us to interpolate between the maximally asymmetric real Ginibre and the Gaussian orthogonal ensemble, as well as their chiral counterparts. (fast track communication)
Embedded random matrix ensembles in quantum physics
Kota, V K B
2014-01-01
Although used with increasing frequency in many branches of physics, random matrix ensembles are not always sufficiently specific to account for important features of the physical system at hand. One refinement which retains the basic stochastic approach but allows for such features consists in the use of embedded ensembles. The present text is an exhaustive introduction to and survey of this important field. Starting with an easy-to-read introduction to general random matrix theory, the text then develops the necessary concepts from the beginning, accompanying the reader to the frontiers of present-day research. With some notable exceptions, to date these ensembles have primarily been applied in nuclear spectroscopy. A characteristic example is the use of a random two-body interaction in the framework of the nuclear shell model. Yet, topics in atomic physics, mesoscopic physics, quantum information science and statistical mechanics of isolated finite quantum systems can also be addressed using these ensemb...
Total probabilities of ensemble runoff forecasts
Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian
2017-04-01
Ensemble forecasting has a long history from meteorological modelling, as an indication of the uncertainty of the forecasts. However, it is necessary to calibrate and post-process the ensembles as the they often exhibit both bias and dispersion errors. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters varying in space and time, while giving a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, which makes it unsuitable for our purpose. Our post-processing method of the ensembles is developed in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu), where we are making forecasts for whole Europe, and based on observations from around 700 catchments. As the target is flood forecasting, we are also more interested in improving the forecast skill for high-flows rather than in a good prediction of the entire flow regime. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different meteorological forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to estimate the total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but we are adding a spatial penalty in the calibration process to force a spatial correlation of the parameters. The penalty takes
Circular β ensembles, CMV representation, characteristic polynomials
Institute of Scientific and Technical Information of China (English)
SU ZhongGen
2009-01-01
In this note we first briefly review some recent progress in the study of the circular β ensemble on the unit circle, where 0 > 0 is a model parameter. In the special cases β = 1,2 and 4, this ensemble describes the joint probability density of eigenvalues of random orthogonal, unitary and sympletic matrices, respectively. For general β, Killip and Nenciu discovered a five-diagonal sparse matrix model, the CMV representation. This representation is new even in the case β = 2; and it has become a powerful tool for studying the circular β ensemble. We then give an elegant derivation for the moment identities of characteristic polynomials via the link with orthogonal polynomials on the unit circle.
Statistical ensembles and fragmentation of finite nuclei
Das, P.; Mallik, S.; Chaudhuri, G.
2017-09-01
Statistical models based on different ensembles are very commonly used to describe the nuclear multifragmentation reaction in heavy ion collisions at intermediate energies. Canonical model results are more appropriate for finite nuclei calculations while those obtained from the grand canonical ones are more easily calculable. A transformation relation has been worked out for converting results of finite nuclei from grand canonical to canonical and vice versa. The formula shows that, irrespective of the particle number fluctuation in the grand canonical ensemble, exact canonical results can be recovered for observables varying linearly or quadratically with the number of particles. This result is of great significance since the baryon and charge conservation constraints can make the exact canonical calculations extremely difficult in general. This concept developed in this work can be extended in future for transformation to ensembles where analytical solutions do not exist. The applicability of certain equations (isoscaling, etc.) in the regime of finite nuclei can also be tested using this transformation relation.
Two-Component Super AKNS Equations and Their Finite-Dimensional Integrable Super Hamiltonian System
Jing Yu; Jingwei Han
2014-01-01
Starting from a matrix Lie superalgebra, two-component super AKNS system is constructed. By making use of monononlinearization technique of Lax pairs, we find that the obtained two-component super AKNS system is a finite-dimensional integrable super Hamiltonian system. And its Lax representation and $r$ -matrix are also given in this paper.
Two-Component Super AKNS Equations and Their Finite-Dimensional Integrable Super Hamiltonian System
Directory of Open Access Journals (Sweden)
Jing Yu
2014-01-01
Full Text Available Starting from a matrix Lie superalgebra, two-component super AKNS system is constructed. By making use of monononlinearization technique of Lax pairs, we find that the obtained two-component super AKNS system is a finite-dimensional integrable super Hamiltonian system. And its Lax representation and r-matrix are also given in this paper.
Subramanian, Aneesh C.; Palmer, Tim N.
2017-06-01
Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.type="synopsis">type="main">Plain Language SummaryProbabilistic weather forecasts, especially for tropical weather, is still a significant challenge for global weather forecasting systems. Expressing uncertainty along with weather forecasts is important for informed decision making. Hence, we explore the use of a relatively new approach in using super-parameterization, where a cloud resolving model is embedded within a global
Ensemble Enabled Weighted PageRank
Luo, Dongsheng; Hu, Renjun; Duan, Liang; Ma, Shuai
2016-01-01
This paper describes our solution for WSDM Cup 2016. Ranking the query independent importance of scholarly articles is a critical and challenging task, due to the heterogeneity and dynamism of entities involved. Our approach is called Ensemble enabled Weighted PageRank (EWPR). To do this, we first propose Time-Weighted PageRank that extends PageRank by introducing a time decaying factor. We then develop an ensemble method to assemble the authorities of the heterogeneous entities involved in scholarly articles. We finally propose to use external data sources to further improve the ranking accuracy. Our experimental study shows that our EWPR is a good choice for ranking scholarly articles.
Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project
Wallick, Michael N.; Mittman, David S.; Shams, Khawaja, S.; Bachmann, Andrew G.; Ludowise, Melissa
2013-01-01
This software simplifies the process of having to set up an Eclipse IDE programming environment for the members of the cross-NASA center project, Ensemble. It achieves this by assembling all the necessary add-ons and custom tools/preferences. This software is unique in that it allows developers in the Ensemble Project (approximately 20 to 40 at any time) across multiple NASA centers to set up a development environment almost instantly and work on Ensemble software. The software automatically has the source code repositories and other vital information and settings included. The Eclipse IDE is an open-source development framework. The NASA (Ensemble-specific) version of the software includes Ensemble-specific plug-ins as well as settings for the Ensemble project. This software saves developers the time and hassle of setting up a programming environment, making sure that everything is set up in the correct manner for Ensemble development. Existing software (i.e., standard Eclipse) requires an intensive setup process that is both time-consuming and error prone. This software is built once by a single user and tested, allowing other developers to simply download and use the software
Highlights from Super-Kamiokande
Okumura, Kimihiro
2016-11-01
Recent results from Super-Kamiokande experiment are reviewed in this paper; Neutrino mass hierarchy and CP violation in the lepton sector are investigated via νμ → νe oscillation of the atmospheric neutrinos. The event rate, correlation with solar activity, energy spectrum of the solar neutrinos are measured via electron elastic scattering interactions. Neutrino emission from the WIMP annihilation at the center of the Sun are searched in the GeV energy regions. New project, SK-Gd project, to enhance anti-neutrino identification capability, has been approved inside the collaboration group.
Highlights from Super-Kamiokande
Directory of Open Access Journals (Sweden)
Okumura Kimihiro
2016-01-01
Full Text Available Recent results from Super-Kamiokande experiment are reviewed in this paper; Neutrino mass hierarchy and CP violation in the lepton sector are investigated via νμ → νe oscillation of the atmospheric neutrinos. The event rate, correlation with solar activity, energy spectrum of the solar neutrinos are measured via electron elastic scattering interactions. Neutrino emission from the WIMP annihilation at the center of the Sun are searched in the GeV energy regions. New project, SK-Gd project, to enhance anti-neutrino identification capability, has been approved inside the collaboration group.
Total probabilities of ensemble runoff forecasts
Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian
2016-04-01
Ensemble forecasting has for a long time been used as a method in meteorological modelling to indicate the uncertainty of the forecasts. However, as the ensembles often exhibit both bias and dispersion errors, it is necessary to calibrate and post-process them. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters which are different in space and time, but still can give a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, and cannot directly be regionalized in the way we would like, so we suggest a different path below. The target of our work is to create a mean forecast with uncertainty bounds for a large number of locations in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu) We are therefore more interested in improving the forecast skill for high-flows rather than the forecast skill of lower runoff levels. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to find a total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but assuring that they have some spatial correlation, by adding a spatial penalty in the calibration process. This can in some cases have a slight negative
Optical trapping with Super-Gaussian beams
CSIR Research Space (South Africa)
McLaren, M
2013-04-01
Full Text Available We outline the possibility of optical trapping and tweezing with Super-Gaussian beam profiles. We show that the trapping strength can be tuned continuously by adjusting the order of a Super-Gaussian beam, approaching that of a perfect Gaussian...
Tetrahedral Units: For Dodecahedral Super-Structures
Ortiz, Y; Liebman, J F
2016-01-01
Different novel organic-chemical possibilities for tetrahedral building units are considered, with attention to their utility in constructing different super-structures. As a representative construction we consider the use of sets of 20 such identical tetrahedral units to form a super-dodecahedron.
An Ensemble Approach for Expanding Queries
2012-11-01
vincristine; thalidomide; painful; cisplatin; oxaliplatin; charcot -marie-tooth disease ; drugs; neuropathy Ensemble expansion child of, asthma, kids...system disorders; peripheral nerve diseases ; peripheral neuropathies; peripheral nervous system disorder; peripheral nervous system disease ...peripheral nerve disease ; peripheral nerve disorders, peripheral nerve disorder Relation expansion offspring, child of, of child, child find
NYYD Ensemble ja Riho Sibul / Anneli Remme
Remme, Anneli, 1968-
2001-01-01
Gavin Bryarsi teos "Jesus' Blood Never Failed Me Yet" NYYD Ensemble'i ja Riho Sibula esituses 27. detsembril Pauluse kirikus Tartus ja 28. detsembril Rootsi- Mihkli kirikus Tallinnas. Kaastegevad Tartu Ülikooli Kammerkoor (Tartus) ja kammerkoor Voces Musicales (Tallinnas). Kunstiline juht Olari Elts
A method for ensemble wildland fire simulation
Mark A. Finney; Isaac C. Grenfell; Charles W. McHugh; Robert C. Seli; Diane Trethewey; Richard D. Stratton; Stuart Brittain
2011-01-01
An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis...
NYYD Ensemble ja Riho Sibul / Anneli Remme
Remme, Anneli, 1968-
2001-01-01
Gavin Bryarsi teos "Jesus' Blood Never Failed Me Yet" NYYD Ensemble'i ja Riho Sibula esituses 27. detsembril Pauluse kirikus Tartus ja 28. detsembril Rootsi- Mihkli kirikus Tallinnas. Kaastegevad Tartu Ülikooli Kammerkoor (Tartus) ja kammerkoor Voces Musicales (Tallinnas). Kunstiline juht Olari Elts
Eigenstate Gibbs ensemble in integrable quantum systems
Nandy, Sourav; Sen, Arnab; Das, Arnab; Dhar, Abhishek
2016-12-01
The eigenstate thermalization hypothesis conjectures that for a thermodynamically large system in one of its energy eigenstates, the reduced density matrix describing any finite subsystem is determined solely by a set of relevant conserved quantities. In a chaotic quantum system, only the energy is expected to play that role and hence eigenstates appear locally thermal. Integrable systems, on the other hand, possess an extensive number of such conserved quantities and therefore the reduced density matrix requires specification of all the corresponding parameters (generalized Gibbs ensemble). However, here we show by unbiased statistical sampling of the individual eigenstates with a given finite energy density that the local description of an overwhelming majority of these states of even such an integrable system is actually Gibbs-like, i.e., requires only the energy density of the eigenstate. Rare eigenstates that cannot be represented by the Gibbs ensemble can also be sampled efficiently by our method and their local properties are then shown to be described by appropriately truncated generalized Gibbs ensembles. We further show that the presence of these rare eigenstates differentiates the model from the chaotic case and leads to the system being described by a generalized Gibbs ensemble at long time under a unitary dynamics following a sudden quench, even when the initial state is a typical (Gibbs-like) eigenstate of the prequench Hamiltonian.
Locally Accessible Information from Multipartite Ensembles
Institute of Scientific and Technical Information of China (English)
SONG Wei
2009-01-01
We present a universal Holevo-like upper bound on the locally accessible information for arbitrary multipartite ensembles.This bound allows us to analyze the indistinguishability of a set of orthogonal states under local operations and classical communication.We also derive the upper bound for the capacity of distributed dense coding with multipartite senders and multipartite receivers.
Canonical Ensemble Model for Black Hole Radiation
Indian Academy of Sciences (India)
Jingyi Zhang
2014-09-01
In this paper, a canonical ensemble model for the black hole quantum tunnelling radiation is introduced. In this model the probability distribution function corresponding to the emission shell is calculated to second order. The formula of pressure and internal energy of the thermal system is modified, and the fundamental equation of thermodynamics is also discussed.
A Hierarchical Bayes Ensemble Kalman Filter
Tsyrulnikov, Michael; Rakitko, Alexander
2017-01-01
A new ensemble filter that allows for the uncertainty in the prior distribution is proposed and tested. The filter relies on the conditional Gaussian distribution of the state given the model-error and predictability-error covariance matrices. The latter are treated as random matrices and updated in a hierarchical Bayes scheme along with the state. The (hyper)prior distribution of the covariance matrices is assumed to be inverse Wishart. The new Hierarchical Bayes Ensemble Filter (HBEF) assimilates ensemble members as generalized observations and allows ordinary observations to influence the covariances. The actual probability distribution of the ensemble members is allowed to be different from the true one. An approximation that leads to a practicable analysis algorithm is proposed. The new filter is studied in numerical experiments with a doubly stochastic one-variable model of "truth". The model permits the assessment of the variance of the truth and the true filtering error variance at each time instance. The HBEF is shown to outperform the EnKF and the HEnKF by Myrseth and Omre (2010) in a wide range of filtering regimes in terms of performance of its primary and secondary filters.
Statistical theory of hierarchical avalanche ensemble
Olemskoi, Alexander I.
1999-01-01
The statistical ensemble of avalanche intensities is considered to investigate diffusion in ultrametric space of hierarchically subordinated avalanches. The stationary intensity distribution and the steady-state current are obtained. The critical avalanche intensity needed to initiate the global avalanche formation is calculated depending on noise intensity. The large time asymptotic for the probability of the global avalanche appearance is derived.
Marking up lattice QCD configurations and ensembles
Coddington, P; Maynard, C M; Pleiter, D; Yoshié, T
2007-01-01
QCDml is an XML-based markup language designed for sharing QCD configurations and ensembles world-wide via the International Lattice Data Grid (ILDG). Based on the latest release, we present key ingredients of the QCDml in order to provide some starting points for colleagues in this community to markup valuable configurations and submit them to the ILDG.
dbSUPER: a database of super-enhancers in mouse and human genome.
Khan, Aziz; Zhang, Xuegong
2016-01-04
Super-enhancers are clusters of transcriptional enhancers that drive cell-type-specific gene expression and are crucial to cell identity. Many disease-associated sequence variations are enriched in super-enhancer regions of disease-relevant cell types. Thus, super-enhancers can be used as potential biomarkers for disease diagnosis and therapeutics. Current studies have identified super-enhancers in more than 100 cell types and demonstrated their functional importance. However, a centralized resource to integrate all these findings is not currently available. We developed dbSUPER (http://bioinfo.au.tsinghua.edu.cn/dbsuper/), the first integrated and interactive database of super-enhancers, with the primary goal of providing a resource for assistance in further studies related to transcriptional control of cell identity and disease. dbSUPER provides a responsive and user-friendly web interface to facilitate efficient and comprehensive search and browsing. The data can be easily sent to Galaxy instances, GREAT and Cistrome web-servers for downstream analysis, and can also be visualized in the UCSC genome browser where custom tracks can be added automatically. The data can be downloaded and exported in variety of formats. Furthermore, dbSUPER lists genes associated with super-enhancers and also links to external databases such as GeneCards, UniProt and Entrez. dbSUPER also provides an overlap analysis tool to annotate user-defined regions. We believe dbSUPER is a valuable resource for the biology and genetic research communities.
A Theoretical Analysis of Why Hybrid Ensembles Work
Directory of Open Access Journals (Sweden)
Kuo-Wei Hsu
2017-01-01
Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.
Global Ensemble Forecast System (GEFS) [2.5 Deg.
National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...
An educational model for ensemble streamflow simulation and uncertainty analysis
National Research Council Canada - National Science Library
AghaKouchak, A; Nakhjiri, N; Habib, E
2013-01-01
...) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity...
Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics
Institute of Scientific and Technical Information of China (English)
Zhaoxia PU; Joshua HACKER
2009-01-01
This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.
Space Applications for Ensemble Detection and Analysis Project
National Aeronautics and Space Administration — Ensemble Detection is both a measurement technique and analysis tool. Like a prism that separates light into spectral bands, an ensemble detector mixes a signal with...
Ensemble-based forecasting at Horns Rev: Ensemble conversion and kernel dressing
DEFF Research Database (Denmark)
Pinson, Pierre; Madsen, Henrik
methodology. In a first stage, ensemble forecasts of meteorological variables are converted to power through a suitable power curve model. The relevance and benefits of employing a newly developed orthogonal fitting method for the power curve model over the traditional least-squares one are discussed...... predictive distributions. Such a methodology has the benefit of yielding predictive distributions that are of increased reliability (in a probabilistic sense) in comparison with the raw ensemble forecasts, while taking advantage of their high resolution....... of probabilistic forecasts, the resolution of which may be maximized by using meteorological ensemble predictions as input. The paper concentrates on the test case of the Horns Rev wind farm over a period of approximately one year, in order to describe, apply and discuss a complete ensemble-based forecasting...
Ending Aging in Super Glassy Polymer Membranes
Energy Technology Data Exchange (ETDEWEB)
Lau, CH; Nguyen, PT; Hill, MR; Thornton, AW; Konstas, K; Doherty, CM; Mulder, RJ; Bourgeois, L; Liu, ACY; Sprouster, DJ; Sullivan, JP; Bastow, TJ; Hill, AJ; Gin, DL; Noble, RD
2014-04-16
Aging in super glassy polymers such as poly(trimethylsilylpropyne) (PTMSP), poly(4-methyl-2-pentyne) (PMP), and polymers with intrinsic microporosity (PIM-1) reduces gas permeabilities and limits their application as gas-separation membranes. While super glassy polymers are initially very porous, and ultra-permeable, they quickly pack into a denser phase becoming less porous and permeable. This age-old problem has been solved by adding an ultraporous additive that maintains the low density, porous, initial stage of super glassy polymers through absorbing a portion of the polymer chains within its pores thereby holding the chains in their open position. This result is the first time that aging in super glassy polymers is inhibited whilst maintaining enhanced CO2 permeability for one year and improving CO2/N-2 selectivity. This approach could allow super glassy polymers to be revisited for commercial application in gas separations.
Theory and Practice of Phase-aware Ensemble Forecasting
Schulte, J. A.; Georgas, N.
2016-12-01
The timing of events represents a source of uncertainty in ensemble forecasting that can produce misleading ensemble statistics. A general theory is presented to overcome drawbacks of traditional ensemble forecasting statistics that perform poorly in the presence of timing disagreements among ensemble members. It was shown, in particular, that ensemble forecasts containing substantial uncertainty in timing can produce non-trivial higher-order statistical moments, rendering the ensemble mean inappropriate as a best available estimate of the future state of the forecast parameter in question. A set of theoretical experiments showed that the existence of large timing differences among ensemble members can produce negative ensemble skewness even when the ensemble members are sinusoids whose amplitudes are drawn from a normal distribution: Consistently, the ensemble mean will tend to fall on the left tail of the normal distribution representing the originally sampled amplitudes, rather than at the mean or median. To remedy the left-tail placement problem of the ensemble mean, a new generally applicable ensemble statistic - the phase-aware ensemble mean - is proposed that is more robust against ensemble skewness resulting from timing spread. The computation of the phase-aware mean involves the transformation of all ensemble members to wavelet space and the subsequent inverse wavelet transformation of the product of the ensemble mean wavelet phase and modulus back to the time domain. The new methods were applied to storm surge reforecasts for Hurricane Irene and Sandy at 8 stations located around the New York City metropolitan area. The phase-aware ensemble mean was found to perform better at detecting the magnitude of events compared to the traditional ensemble mean, consistent with the results from theoretical experiments. The ensemble mean, moreover, was found to be consistently located on the left tail of distributions representing future peak storm surge outcomes. A
Quantum canonical ensemble: A projection operator approach
Magnus, Wim; Lemmens, Lucien; Brosens, Fons
2017-09-01
Knowing the exact number of particles N, and taking this knowledge into account, the quantum canonical ensemble imposes a constraint on the occupation number operators. The constraint particularly hampers the systematic calculation of the partition function and any relevant thermodynamic expectation value for arbitrary but fixed N. On the other hand, fixing only the average number of particles, one may remove the above constraint and simply factorize the traces in Fock space into traces over single-particle states. As is well known, that would be the strategy of the grand-canonical ensemble which, however, comes with an additional Lagrange multiplier to impose the average number of particles. The appearance of this multiplier can be avoided by invoking a projection operator that enables a constraint-free computation of the partition function and its derived quantities in the canonical ensemble, at the price of an angular or contour integration. Introduced in the recent past to handle various issues related to particle-number projected statistics, the projection operator approach proves beneficial to a wide variety of problems in condensed matter physics for which the canonical ensemble offers a natural and appropriate environment. In this light, we present a systematic treatment of the canonical ensemble that embeds the projection operator into the formalism of second quantization while explicitly fixing N, the very number of particles rather than the average. Being applicable to both bosonic and fermionic systems in arbitrary dimensions, transparent integral representations are provided for the partition function ZN and the Helmholtz free energy FN as well as for two- and four-point correlation functions. The chemical potential is not a Lagrange multiplier regulating the average particle number but can be extracted from FN+1 -FN, as illustrated for a two-dimensional fermion gas.
Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast
Jinyin Ye; Yuehong Shao; Zhijia Li
2016-01-01
TIGGE (THORPEX International Grand Global Ensemble) was a major part of the THORPEX (Observing System Research and Predictability Experiment). It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability fo...
Ensembles of signal transduction models using Pareto Optimal Ensemble Techniques (POETs).
Song, Sang Ok; Chakrabarti, Anirikh; Varner, Jeffrey D
2010-07-01
Mathematical modeling of complex gene expression programs is an emerging tool for understanding disease mechanisms. However, identification of large models sometimes requires training using qualitative, conflicting or even contradictory data sets. One strategy to address this challenge is to estimate experimentally constrained model ensembles using multiobjective optimization. In this study, we used Pareto Optimal Ensemble Techniques (POETs) to identify a family of proof-of-concept signal transduction models. POETs integrate Simulated Annealing (SA) with Pareto optimality to identify models near the optimal tradeoff surface between competing training objectives. We modeled a prototypical-signaling network using mass-action kinetics within an ordinary differential equation (ODE) framework (64 ODEs in total). The true model was used to generate synthetic immunoblots from which the POET algorithm identified the 117 unknown model parameters. POET generated an ensemble of signaling models, which collectively exhibited population-like behavior. For example, scaled gene expression levels were approximately normally distributed over the ensemble following the addition of extracellular ligand. Also, the ensemble recovered robust and fragile features of the true model, despite significant parameter uncertainty. Taken together, these results suggest that experimentally constrained model ensembles could capture qualitatively important network features without exact parameter information.
Data assimilation in integrated hydrological modeling using ensemble Kalman filtering
DEFF Research Database (Denmark)
Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh
2015-01-01
Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...
Exploring and Listening to Chinese Classical Ensembles in General Music
Zhang, Wenzhuo
2017-01-01
Music diversity is valued in theory, but the extent to which it is efficiently presented in music class remains limited. Within this article, I aim to bridge this gap by introducing four genres of Chinese classical ensembles--Qin and Xiao duets, Jiang Nan bamboo and silk ensembles, Cantonese ensembles, and contemporary Chinese orchestras--into the…
Data assimilation in integrated hydrological modeling using ensemble Kalman filtering
DEFF Research Database (Denmark)
Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh;
2015-01-01
Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...
The role of ensemble post-processing for modeling the ensemble tail
Van De Vyver, Hans; Van Schaeybroeck, Bert; Vannitsem, Stéphane
2016-04-01
The past decades the numerical weather prediction community has witnessed a paradigm shift from deterministic to probabilistic forecast and state estimation (Buizza and Leutbecher, 2015; Buizza et al., 2008), in an attempt to quantify the uncertainties associated with initial-condition and model errors. An important benefit of a probabilistic framework is the improved prediction of extreme events. However, one may ask to what extent such model estimates contain information on the occurrence probability of extreme events and how this information can be optimally extracted. Different approaches have been proposed and applied on real-world systems which, based on extreme value theory, allow the estimation of extreme-event probabilities conditional on forecasts and state estimates (Ferro, 2007; Friederichs, 2010). Using ensemble predictions generated with a model of low dimensionality, a thorough investigation is presented quantifying the change of predictability of extreme events associated with ensemble post-processing and other influencing factors including the finite ensemble size, lead time and model assumption and the use of different covariates (ensemble mean, maximum, spread...) for modeling the tail distribution. Tail modeling is performed by deriving extreme-quantile estimates using peak-over-threshold representation (generalized Pareto distribution) or quantile regression. Common ensemble post-processing methods aim to improve mostly the ensemble mean and spread of a raw forecast (Van Schaeybroeck and Vannitsem, 2015). Conditional tail modeling, on the other hand, is a post-processing in itself, focusing on the tails only. Therefore, it is unclear how applying ensemble post-processing prior to conditional tail modeling impacts the skill of extreme-event predictions. This work is investigating this question in details. Buizza, Leutbecher, and Isaksen, 2008: Potential use of an ensemble of analyses in the ECMWF Ensemble Prediction System, Q. J. R. Meteorol
Demonstrating the value of larger ensembles in forecasting physical systems
Directory of Open Access Journals (Sweden)
Reason L. Machete
2016-12-01
Full Text Available Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying variations in the sensitivity of the model all the way to providing actionable probability forecasts of the future. Whatever the goal is, success depends on the properties of the ensemble, and there is a longstanding discussion in meteorology as to the size of initial condition ensemble most appropriate for Numerical Weather Prediction. In terms of resource allocation: how is one to divide finite computing resources between model complexity, ensemble size, data assimilation and other components of the forecast system. One wishes to avoid undersampling information available from the model's dynamics, yet one also wishes to use the highest fidelity model available. Arguably, a higher fidelity model can better exploit a larger ensemble; nevertheless it is often suggested that a relatively small ensemble, say ~16 members, is sufficient and that larger ensembles are not an effective investment of resources. This claim is shown to be dubious when the goal is probabilistic forecasting, even in settings where the forecast model is informative but imperfect. Probability forecasts for a ‘simple’ physical system are evaluated at different lead times; ensembles of up to 256 members are considered. The pure density estimation context (where ensemble members are drawn from the same underlying distribution as the target differs from the forecasting context, where one is given a high fidelity (but imperfect model. In the forecasting context, the information provided by additional members depends also on the fidelity of the model, the ensemble formation scheme (data assimilation, the ensemble interpretation and the nature of the observational noise. The effect of increasing the ensemble size is quantified by
SuperB Progress Report for Physics
Energy Technology Data Exchange (ETDEWEB)
O' Leary, B.; /Aachen, Tech. Hochsch.; Matias, J.; Ramon, M.; /Barcelona, IFAE; Pous, E.; /Barcelona U.; De Fazio, F.; Palano, A.; /INFN, Bari; Eigen, G.; /Bergen U.; Asgeirsson, D.; /British Columbia U.; Cheng, C.H.; Chivukula, A.; Echenard, B.; Hitlin, D.G.; Porter, F.; Rakitin, A.; /Caltech; Heinemeyer, S.; /Cantabria Inst. of Phys.; McElrath, B.; /CERN; Andreassen, R.; Meadows, B.; Sokoloff, M.; /Cincinnati U.; Blanke, M.; /Cornell U., Phys. Dept.; Lesiak, T.; /Cracow, INP /DESY /Zurich, ETH /INFN, Ferrara /Frascati /INFN, Genoa /Glasgow U. /Indiana U. /Mainz U., Inst. Phys. /Karlsruhe, Inst. Technol. /KEK, Tsukuba /LBL, Berkeley /UC, Berkeley /Lisbon, IST /Ljubljana U. /Madrid, Autonoma U. /Maryland U. /MIT /INFN, Milan /McGill U. /Munich, Tech. U. /Notre Dame U. /PNL, Richland /INFN, Padua /Paris U., VI-VII /Orsay, LAL /Orsay, LPT /INFN, Pavia /INFN, Perugia /INFN, Pisa /Queen Mary, U. of London /Regensburg U. /Republica U., Montevideo /Frascati /INFN, Rome /INFN, Rome /INFN, Rome /Rutherford /Sassari U. /Siegen U. /SLAC /Southern Methodist U. /Tel Aviv U. /Tohoku U. /INFN, Turin /INFN, Trieste /Uppsala U. /Valencia U., IFIC /Victoria U. /Wayne State U. /Wisconsin U., Madison
2012-02-14
SuperB is a high luminosity e{sup +}e{sup -} collider that will be able to indirectly probe new physics at energy scales far beyond the reach of any man made accelerator planned or in existence. Just as detailed understanding of the Standard Model of particle physics was developed from stringent constraints imposed by flavour changing processes between quarks, the detailed structure of any new physics is severely constrained by flavour processes. In order to elucidate this structure it is necessary to perform a number of complementary studies of a set of golden channels. With these measurements in hand, the pattern of deviations from the Standard Model behavior can be used as a test of the structure of new physics. If new physics is found at the LHC, then the many golden measurements from SuperB will help decode the subtle nature of the new physics. However if no new particles are found at the LHC, SuperB will be able to search for new physics at energy scales up to 10-100 TeV. In either scenario, flavour physics measurements that can be made at SuperB play a pivotal role in understanding the nature of physics beyond the Standard Model. Examples for using the interplay between measurements to discriminate New Physics models are discussed in this document. SuperB is a Super Flavour Factory, in addition to studying large samples of B{sub u,d,s}, D and {tau} decays, SuperB has a broad physics programme that includes spectroscopy both in terms of the Standard Model and exotica, and precision measurements of sin{sup 2} {theta}{sub W}. In addition to performing CP violation measurements at the {Upsilon}(4S) and {phi}(3770), SuperB will test CPT in these systems, and lepton universality in a number of different processes. The multitude of rare decay measurements possible at SuperB can be used to constrain scenarios of physics beyond the Standard Model. In terms of other precision tests of the Standard Model, this experiment will be able to perform precision over
The superB silicon vertex tracker
Energy Technology Data Exchange (ETDEWEB)
Rizzo, G., E-mail: giuliana.rizzo@pi.infn.i [INFN-Pisa and Universita di Pisa (Italy); Avanzini, C.; Batignani, G.; Bettarini, S.; Bosi, F.; Calderini, G.; Ceccanti, M.; Cenci, R.; Cervelli, A.; Crescioli, F.; Dell' Orso, M.; Forti, F.; Giannetti, P.; Giorgi, M.A. [INFN-Pisa and Universita di Pisa (Italy); Lusiani, A. [Scuola Normale Superiore and INFN-Pisa (Italy); Gregucci, S.; Mammini, P.; Marchiori, G.; Massa, M.; Morsani, F. [INFN-Pisa and Universita di Pisa (Italy)
2010-05-21
The SuperB asymmetric e{sup +}-e{sup -} collider has been designed to deliver a luminosity greater than 10{sup 36}cm{sup -2}s{sup -1} with moderate beam currents. Comparing to current B-Factories, the reduced center of mass boost of the SuperB machine requires improved vertex resolution to allow precision measurements sensitive to New Physics. We present the conceptual design of the silicon vertex tracker (SVT) for the SuperB detector with the present status of the R and D on the different options under study for its innermost Layer0.
Ensemble Forecasting of Major Solar Flares
Guerra, J A; Uritsky, V M
2015-01-01
We present the results from the first ensemble prediction model for major solar flares (M and X classes). Using the probabilistic forecasts from three models hosted at the Community Coordinated Modeling Center (NASA-GSFC) and the NOAA forecasts, we developed an ensemble forecast by linearly combining the flaring probabilities from all four methods. Performance-based combination weights were calculated using a Monte Carlo-type algorithm by applying a decision threshold $P_{th}$ to the combined probabilities and maximizing the Heidke Skill Score (HSS). Using the probabilities and events time series from 13 recent solar active regions (2012 - 2014), we found that a linear combination of probabilities can improve both probabilistic and categorical forecasts. Combination weights vary with the applied threshold and none of the tested individual forecasting models seem to provide more accurate predictions than the others for all values of $P_{th}$. According to the maximum values of HSS, a performance-based weights ...
Quantum data compression of a qubit ensemble.
Rozema, Lee A; Mahler, Dylan H; Hayat, Alex; Turner, Peter S; Steinberg, Aephraim M
2014-10-17
Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the extreme difficulty involved in creating reliable quantum memories. We present a protocol in which an ensemble of quantum bits (qubits) can in principle be perfectly compressed into exponentially fewer qubits. We then experimentally implement our algorithm, compressing three photonic qubits into two. This protocol sheds light on the subtle differences between quantum and classical information. Furthermore, since data compression stores all of the available information about the quantum state in fewer physical qubits, it could allow for a vast reduction in the amount of quantum memory required to store a quantum ensemble, making even today's limited quantum memories far more powerful than previously recognized.
Rotationally invariant ensembles of integrable matrices.
Yuzbashyan, Emil A; Shastry, B Sriram; Scaramazza, Jasen A
2016-05-01
We construct ensembles of random integrable matrices with any prescribed number of nontrivial integrals and formulate integrable matrix theory (IMT)-a counterpart of random matrix theory (RMT) for quantum integrable models. A type-M family of integrable matrices consists of exactly N-M independent commuting N×N matrices linear in a real parameter. We first develop a rotationally invariant parametrization of such matrices, previously only constructed in a preferred basis. For example, an arbitrary choice of a vector and two commuting Hermitian matrices defines a type-1 family and vice versa. Higher types similarly involve a random vector and two matrices. The basis-independent formulation allows us to derive the joint probability density for integrable matrices, similar to the construction of Gaussian ensembles in the RMT.
Face Recognition using Optimal Representation Ensemble
Li, Hanxi; Gao, Yongsheng
2011-01-01
Recently, the face recognizers based on linear representations have been shown to deliver state-of-the-art performance. In real-world applications, however, face images usually suffer from expressions, disguises and random occlusions. The problematic facial parts undermine the validity of the linear-subspace assumption and thus the recognition performance deteriorates significantly. In this work, we address the problem in a learning-inference-mixed fashion. By observing that the linear-subspace assumption is more reliable on certain face patches rather than on the holistic face, some Bayesian Patch Representations (BPRs) are randomly generated and interpreted according to the Bayes' theory. We then train an ensemble model over the patch-representations by minimizing the empirical risk w.r.t the "leave-one-out margins". The obtained model is termed Optimal Representation Ensemble (ORE), since it guarantees the optimality from the perspective of Empirical Risk Minimization. To handle the unknown patterns in tes...
Statistical ensembles for money and debt
Viaggiu, Stefano; Lionetto, Andrea; Bargigli, Leonardo; Longo, Michele
2012-10-01
We build a statistical ensemble representation of two economic models describing respectively, in simplified terms, a payment system and a credit market. To this purpose we adopt the Boltzmann-Gibbs distribution where the role of the Hamiltonian is taken by the total money supply (i.e. including money created from debt) of a set of interacting economic agents. As a result, we can read the main thermodynamic quantities in terms of monetary ones. In particular, we define for the credit market model a work term which is related to the impact of monetary policy on credit creation. Furthermore, with our formalism we recover and extend some results concerning the temperature of an economic system, previously presented in the literature by considering only the monetary base as a conserved quantity. Finally, we study the statistical ensemble for the Pareto distribution.
Staying thermal with Hartree ensemble approximations
Energy Technology Data Exchange (ETDEWEB)
Salle, Mischa E-mail: msalle@science.uva.nl; Smit, Jan E-mail: jsmit@science.uva.nl; Vink, Jeroen C. E-mail: jcvink@science.uva.nl
2002-03-25
We study thermal behavior of a recently introduced Hartree ensemble approximation, which allows for non-perturbative inhomogeneous field configurations as well as for approximate thermalization, in the phi (cursive,open) Greek{sup 4} model in 1+1 dimensions. Using ensembles with a free field thermal distribution as out-of-equilibrium initial conditions we determine thermalization time scales. The time scale for which the system stays in approximate quantum thermal equilibrium is an indication of the time scales for which the approximation method stays reasonable. This time scale turns out to be two orders of magnitude larger than the time scale for thermalization, in the range of couplings and temperatures studied. We also discuss simplifications of our method which are numerically more efficient and make a comparison with classical dynamics.
Entanglement in a Solid State Spin Ensemble
Simmons, Stephanie; Riemann, Helge; Abrosimov, Nikolai V; Becker, Peter; Pohl, Hans-Joachim; Thewalt, Mike L W; Itoh, Kohei M; Morton, John J L
2010-01-01
Entanglement is the quintessential quantum phenomenon and a necessary ingredient in most emerging quantum technologies, including quantum repeaters, quantum information processing (QIP) and the strongest forms of quantum cryptography. Spin ensembles, such as those in liquid state nuclear magnetic resonance, have been powerful in the development of quantum control methods, however, these demonstrations contained no entanglement and ultimately constitute classical simulations of quantum algorithms. Here we report the on-demand generation of entanglement between an ensemble of electron and nuclear spins in isotopically engineered phosphorus-doped silicon. We combined high field/low temperature electron spin resonance (3.4 T, 2.9 K) with hyperpolarisation of the 31P nuclear spin to obtain an initial state of sufficient purity to create a non-classical, inseparable state. The state was verified using density matrix tomography based on geometric phase gates, and had a fidelity of 98% compared with the ideal state a...
Dysonian dynamics of the Ginibre ensemble.
Burda, Zdzislaw; Grela, Jacek; Nowak, Maciej A; Tarnowski, Wojciech; Warchoł, Piotr
2014-09-05
We study the time evolution of Ginibre matrices whose elements undergo Brownian motion. The non-Hermitian character of the Ginibre ensemble binds the dynamics of eigenvalues to the evolution of eigenvectors in a nontrivial way, leading to a system of coupled nonlinear equations resembling those for turbulent systems. We formulate a mathematical framework allowing simultaneous description of the flow of eigenvalues and eigenvectors, and we unravel a hidden dynamics as a function of a new complex variable, which in the standard description is treated as a regulator only. We solve the evolution equations for large matrices and demonstrate that the nonanalytic behavior of the Green's functions is associated with a shock wave stemming from a Burgers-like equation describing correlations of eigenvectors. We conjecture that the hidden dynamics that we observe for the Ginibre ensemble is a general feature of non-Hermitian random matrix models and is relevant to related physical applications.
Rotationally invariant ensembles of integrable matrices
Yuzbashyan, Emil A.; Shastry, B. Sriram; Scaramazza, Jasen A.
2016-05-01
We construct ensembles of random integrable matrices with any prescribed number of nontrivial integrals and formulate integrable matrix theory (IMT)—a counterpart of random matrix theory (RMT) for quantum integrable models. A type-M family of integrable matrices consists of exactly N -M independent commuting N ×N matrices linear in a real parameter. We first develop a rotationally invariant parametrization of such matrices, previously only constructed in a preferred basis. For example, an arbitrary choice of a vector and two commuting Hermitian matrices defines a type-1 family and vice versa. Higher types similarly involve a random vector and two matrices. The basis-independent formulation allows us to derive the joint probability density for integrable matrices, similar to the construction of Gaussian ensembles in the RMT.
Eigenstate Gibbs Ensemble in Integrable Quantum Systems
Nandy, Sourav; Das, Arnab; Dhar, Abhishek
2016-01-01
The Eigenstate Thermalization Hypothesis implies that for a thermodynamically large system in one of its eigenstates, the reduced density matrix describing any finite subsystem is determined solely by a set of {\\it relevant} conserved quantities. In a generic system, only the energy plays that role and hence eigenstates appear locally thermal. Integrable systems, on the other hand, possess an extensive number of such conserved quantities and hence the reduced density matrix requires specification of an infinite number of parameters (Generalized Gibbs Ensemble). However, here we show by unbiased statistical sampling of the individual eigenstates with a given finite energy density, that the local description of an overwhelming majority of these states of even such an integrable system is actually Gibbs-like, i.e. requires only the energy density of the eigenstate. Rare eigenstates that cannot be represented by the Gibbs ensemble can also be sampled efficiently by our method and their local properties are then s...
ABCD of Beta Ensembles and Topological Strings
Krefl, Daniel
2012-01-01
We study beta-ensembles with Bn, Cn, and Dn eigenvalue measure and their relation with refined topological strings. Our results generalize the familiar connections between local topological strings and matrix models leading to An measure, and illustrate that all those classical eigenvalue ensembles, and their topological string counterparts, are related one to another via various deformations and specializations, quantum shifts and discrete quotients. We review the solution of the Gaussian models via Macdonald identities, and interpret them as conifold theories. The interpolation between the various models is plainly apparent in this case. For general polynomial potential, we calculate the partition function in the multi-cut phase in a perturbative fashion, beyond tree-level in the large-N limit. The relation to refined topological string orientifolds on the corresponding local geometry is discussed along the way.
Support Vector Machine Ensemble Based on Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
LI Ye; YIN Ru-po; CAI Yun-ze; XU Xiao-ming
2006-01-01
Support vector machines (SVMs) have been introduced as effective methods for solving classification problems.However, due to some limitations in practical applications,their generalization performance is sometimes far from the expected level. Therefore, it is meaningful to study SVM ensemble learning. In this paper, a novel genetic algorithm based ensemble learning method, namely Direct Genetic Ensemble (DGE), is proposed. DGE adopts the predictive accuracy of ensemble as the fitness function and searches a good ensemble from the ensemble space. In essence, DGE is also a selective ensemble learning method because the base classifiers of the ensemble are selected according to the solution of genetic algorithm. In comparison with other ensemble learning methods, DGE works on a higher level and is more direct. Different strategies of constructing diverse base classifiers can be utilized in DGE.Experimental results show that SVM ensembles constructed by DGE can achieve better performance than single SVMs,bagged and boosted SVM ensembles. In addition, some valuable conclusions are obtained.
Various multistage ensembles for prediction of heating energy consumption
Directory of Open Access Journals (Sweden)
Radisa Jovanovic
2015-04-01
Full Text Available Feedforward neural network models are created for prediction of daily heating energy consumption of a NTNU university campus Gloshaugen using actual measured data for training and testing. Improvement of prediction accuracy is proposed by using neural network ensemble. Previously trained feed-forward neural networks are first separated into clusters, using k-means algorithm, and then the best network of each cluster is chosen as member of an ensemble. Two conventional averaging methods for obtaining ensemble output are applied; simple and weighted. In order to achieve better prediction results, multistage ensemble is investigated. As second level, adaptive neuro-fuzzy inference system with various clustering and membership functions are used to aggregate the selected ensemble members. Feedforward neural network in second stage is also analyzed. It is shown that using ensemble of neural networks can predict heating energy consumption with better accuracy than the best trained single neural network, while the best results are achieved with multistage ensemble.
Spatially Coupled Ensembles Universally Achieve Capacity under Belief Propagation
Kudekar, Shrinivas; Urbanke, Ruediger
2012-01-01
We investigate spatially coupled code ensembles. For transmission over the binary erasure channel, it was recently shown that spatial coupling increases the belief propagation threshold of the ensemble to essentially the maximum a-priori threshold of the underlying component ensemble. This explains why convolutional LDPC ensembles, originally introduced by Felstrom and Zigangirov, perform so well over this channel. We show that the equivalent result holds true for transmission over general binary-input memoryless output-symmetric channels. More precisely, given a desired error probability and a gap to capacity, we can construct a spatially coupled ensemble which fulfills these constraints universally on this class of channels under belief propagation decoding. In fact, most codes in that ensemble have that property. The quantifier universal refers to the single ensemble/code which is good for all channels but we assume that the channel is known at the receiver. The key technical result is a proof that under b...
Analysis and optimization of weighted ensemble sampling
Aristoff, David
2016-01-01
We give a mathematical framework for weighted ensemble (WE) sampling, a binning and resampling technique for efficiently computing probabilities in molecular dynamics. We prove that WE sampling is unbiased in a very general setting that includes adaptive binning. We show that when WE is used for stationary calculations in tandem with a Markov state model (MSM), the MSM can be used to optimize the allocation of replicas in the bins.
Quantum Data Compression of a Qubit Ensemble
Rozema, Lee A.; Mahler, Dylan H.; Hayat, Alex; Turner, Peter S.; Steinberg, Aephraim M.
2014-01-01
Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the extreme difficulty involved in creating reliable quantum memories. We present a protocol in which an ensemble of quantum bits (qubits) can in principle be perfectly compressed into exponentially fewer qubits. We then experimentally implement our algorithm, compre...
Multiscale ensemble filtering for reservoir engineering applications
Lawniczak, W.; Hanea, R.G.; Heemink, A.; Mclaughlin, D.
2009-01-01
Reservoir management requires periodic updates of the simulation models using the production data available over time. Traditionally, validation of reservoir models with production data is done using a history matching process. Uncertainties in the data, as well as in the model, lead to a nonunique history matching inverse problem. It has been shown that the ensemble Kalman filter (EnKF) is an adequate method for predicting the dynamics of the reservoir. The EnKF is a sequential Monte-Carlo a...
Statistical Ensemble Theory of Gompertz Growth Model
Directory of Open Access Journals (Sweden)
Takuya Yamano
2009-11-01
Full Text Available An ensemble formulation for the Gompertz growth function within the framework of statistical mechanics is presented, where the two growth parameters are assumed to be statistically distributed. The growth can be viewed as a self-referential process, which enables us to use the Bose-Einstein statistics picture. The analytical entropy expression pertain to the law can be obtained in terms of the growth velocity distribution as well as the Gompertz function itself for the whole process.
Staying Thermal with Hartree Ensemble Approximations
Salle, M; Vink, Jeroen C
2000-01-01
Using Hartree ensemble approximations to compute the real time dynamics of scalar fields in 1+1 dimension, we find that with suitable initial conditions, approximate thermalization is achieved much faster than found in our previous work. At large times, depending on the interaction strength and temperature, the particle distribution slowly changes: the Bose-Einstein distribution of the particle densities develops classical features. We also discuss variations of our method which are numerically more efficient.
N=2 Super - $W_{3}$ Algebra and N=2 Super Boussinesq Equations
Ivanov, E; Malik, R P
1995-01-01
We study classical $N=2$ super-$W_3$ algebra and its interplay with $N=2$ supersymmetric extensions of the Boussinesq equation in the framework of the nonlinear realization method and the inverse Higgs - covariant reduction approach. These techniques have been previously applied by us in the bosonic $W_3$ case to give a new geometric interpretation of the Boussinesq hierarchy. Here we deduce the most general $N=2$ super Boussinesq equation and two kinds of the modified $N=2$ super Boussinesq equations, as well as the super Miura maps relating these systems to each other, by applying the covariant reduction to certain coset manifolds of linear $N=2$ super-$W_3^{\\infty}$ symmetry associated with $N=2$ super-$W_3$. We discuss the integrability properties of the equations obtained and their correspondence with the formulation based on the notion of the second hamiltonian structure.
Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale
Parton, Daniel L.; Grinaway, Patrick B.; Hanson, Sonya M.; Beauchamp, Kyle A.; Chodera, John D.
2016-01-01
The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (super)families, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences—from a single sequence to an entire superfamily—and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest), reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics—such as Markov state models (MSMs)—which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human tyrosine
Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale.
Parton, Daniel L; Grinaway, Patrick B; Hanson, Sonya M; Beauchamp, Kyle A; Chodera, John D
2016-06-01
The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (super)families, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences-from a single sequence to an entire superfamily-and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest), reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics-such as Markov state models (MSMs)-which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human tyrosine kinase
Interplanetary magnetic field ensemble at 1 AU
Energy Technology Data Exchange (ETDEWEB)
Matthaeus, W.H.; Goldstein, M.L.; King, J.H.
1985-04-01
A method for calculation ensemble averages from magnetic field data is described. A data set comprising approximately 16 months of nearly continuous ISEE-3 magnetic field data is used in this study. Individual subintervals of this data, ranging from 15 hours to 15.6 days comprise the ensemble. The sole condition for including each subinterval in the averages is the degree to which it represents a weakly time-stationary process. Averages obtained by this method are appropriate for a turbulence description of the interplanetary medium. The ensemble average correlation length obtained from all subintervals is found to be 4.9 x 10 to the 11th cm. The average value of the variances of the magnetic field components are in the approximate ratio 8:9:10, where the third component is the local mean field direction. The correlation lengths and variances are found to have a systematic variation with subinterval duration, reflecting the important role of low-frequency fluctuations in the interplanetary medium.
Gradient Flow Analysis on MILC HISQ Ensembles
Energy Technology Data Exchange (ETDEWEB)
Brown, Nathan [Washington U., St. Louis; Bazavov, Alexei [Brookhaven; Bernard, Claude [Washington U., St. Louis; DeTar, Carleton [Utah U.; Foley, Justin [Utah U.; Gottlieb, Steven [Indiana U.; Heller, Urs M. [APS, New York; Hetrick, J. E. [U. Pacific, Stockton; Komijani, Javad [Washington U., St. Louis; Laiho, Jack [Syracuse U.; Levkova, Ludmila [Utah U.; Oktay, M. B. [Utah U.; Sugar, Robert [UC, Santa Barbara; Toussaint, Doug [Arizona U.; Van de Water, Ruth S. [Fermilab; Zhou, Ran [Fermilab
2014-11-14
We report on a preliminary scale determination with gradient-flow techniques on the $N_f = 2 + 1 + 1$ HISQ ensembles generated by the MILC collaboration. The ensembles include four lattice spacings, ranging from 0.15 to 0.06 fm, and both physical and unphysical values of the quark masses. The scales $\\sqrt{t_0}/a$ and $w_0/a$ are computed using Symanzik flow and the cloverleaf definition of $\\langle E \\rangle$ on each ensemble. Then both scales and the meson masses $aM_\\pi$ and $aM_K$ are adjusted for mistunings in the charm mass. Using a combination of continuum chiral perturbation theory and a Taylor series ansatz in the lattice spacing, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. Our preliminary results are $\\sqrt{t_0} = 0.1422(7)$fm and $w_0 = 0.1732(10)$fm. We also find the continuum mass-dependence of $w_0$.
Cavity Cooling for Ensemble Spin Systems
Cory, David
2015-03-01
Recently there has been a surge of interest in exploring thermodynamics in quantum systems where dissipative effects can be exploited to perform useful work. One such example is quantum state engineering where a quantum state of high purity may be prepared by dissipative coupling through a cold thermal bath. This has been used to great effect in many quantum systems where cavity cooling has been used to cool mechanical modes to their quantum ground state through coupling to the resolved sidebands of a high-Q resonator. In this talk we explore how these techniques may be applied to an ensemble spin system. This is an attractive process as it potentially allows for parallel remove of entropy from a large number of quantum systems, enabling an ensemble to achieve a polarization greater than thermal equilibrium, and potentially on a time scale much shorter than thermal relaxation processes. This is achieved by the coupled angular momentum subspaces of the ensemble behaving as larger effective spins, overcoming the weak individual coupling of individual spins to a microwave resonator. Cavity cooling is shown to cool each of these subspaces to their respective ground state, however an additional algorithmic step or dissipative process is required to couple between these subspaces and enable cooling to the full ground state of the joint system.
Multivariate localization methods for ensemble Kalman filtering
Roh, S.
2015-05-08
In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Gradient Flow Analysis on MILC HISQ Ensembles
Bazavov, A; Brown, N; DeTar, C; Foley, J; Gottlieb, Steven; Heller, U M; Hetrick, J E; Komijani, J; Laiho, J; Levkova, L; Oktay, M; Sugar, R L; Toussaint, D; Van de Water, R S; Zhou, R
2014-01-01
We report on a preliminary scale determination with gradient-flow techniques on the $N_f = 2 + 1 + 1$ HISQ ensembles generated by the MILC collaboration. The ensembles include four lattice spacings, ranging from 0.15 to 0.06 fm, and both physical and unphysical values of the quark masses. The scales $\\sqrt{t_0}/a$ and $w_0/a$ are computed using Symanzik flow and the cloverleaf definition of $\\langle E \\rangle$ on each ensemble. Then both scales and the meson masses $aM_\\pi$ and $aM_K$ are adjusted for mistunings in the charm mass. Using a combination of continuum chiral perturbation theory and a Taylor series ansatz in the lattice spacing, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. Our preliminary results are $\\sqrt{t_0} = 0.1422(7)$fm and $w_0 = 0.1732(10)$fm. We also find the continuum mass-dependence of $w_0$.
Multivariate localization methods for ensemble Kalman filtering
Roh, S.
2015-12-03
In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Ensemble transform sensitivity method for adaptive observations
Zhang, Yu; Xie, Yuanfu; Wang, Hongli; Chen, Dehui; Toth, Zoltan
2016-01-01
The Ensemble Transform (ET) method has been shown to be useful in providing guidance for adaptive observation deployment. It predicts forecast error variance reduction for each possible deployment using its corresponding transformation matrix in an ensemble subspace. In this paper, a new ET-based sensitivity (ETS) method, which calculates the gradient of forecast error variance reduction in terms of analysis error variance reduction, is proposed to specify regions for possible adaptive observations. ETS is a first order approximation of the ET; it requires just one calculation of a transformation matrix, increasing computational efficiency (60%-80% reduction in computational cost). An explicit mathematical formulation of the ETS gradient is derived and described. Both the ET and ETS methods are applied to the Hurricane Irene (2011) case and a heavy rainfall case for comparison. The numerical results imply that the sensitive areas estimated by the ETS and ET are similar. However, ETS is much more efficient, particularly when the resolution is higher and the number of ensemble members is larger.
Multivariate localization methods for ensemble Kalman filtering
Directory of Open Access Journals (Sweden)
S. Roh
2015-05-01
Full Text Available In ensemble Kalman filtering (EnKF, the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
On large deviations for ensembles of distributions
Energy Technology Data Exchange (ETDEWEB)
Khrychev, D A [Moscow State Institute of Radio-Engineering, Electronics and Automation (Technical University), Moscow (Russian Federation)
2013-11-30
The paper is concerned with the large deviations problem in the Freidlin-Wentzell formulation without the assumption of the uniqueness of the solution to the equation involving white noise. In other words, it is assumed that for each ε>0 the nonempty set P{sub ε} of weak solutions is not necessarily a singleton. Analogues of a number of concepts in the theory of large deviations are introduced for the set (P{sub ε}, ε>0), hereafter referred to as an ensemble of distributions. The ensembles of weak solutions of an n-dimensional stochastic Navier-Stokes system and stochastic wave equation with power-law nonlinearity are shown to be uniformly exponentially tight. An idempotent Wiener process in a Hilbert space and idempotent partial differential equations are defined. The accumulation points in the sense of large deviations of the ensembles in question are shown to be weak solutions of the corresponding idempotent equations. Bibliography: 14 titles.
Multivariate localization methods for ensemble Kalman filtering
Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.
2015-12-01
In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Dynamic Analogue Initialization for Ensemble Forecasting
Institute of Scientific and Technical Information of China (English)
LI Shan; RONG Xingyao; LIU Yun; LIU Zhengyu; Klaus FRAEDRICH
2013-01-01
This paper introduces a new approach for the initialization of ensemble numerical forecasting:Dynamic Analogue Initialization (DAI).DAI assumes that the best model state trajectories for the past provide the initial conditions for the best forecasts in the future.As such,DAI performs the ensemble forecast using the best analogues from a full size ensemble.As a pilot study,the Lorenz63 and Lorenz96 models were used to test DAI's effectiveness independently.Results showed that DAI can improve the forecast significantly.Especially in lower-dimensional systems,DAI can reduce the forecast RMSE by ～50％ compared to the Monte Carlo forecast (MC).This improvement is because DAI is able to recognize the direction of the analysis error through the embedding process and therefore selects those good trajectories with reduced initial error.Meanwhile,a potential improvement of DAI is also proposed,and that is to find the optimal range of embedding time based on the error's growing speed.
Phase transitions in ensembles of solitons induced by an optical pumping or a strong electric field
Karpov, P.; Brazovskii, S.
2016-09-01
The latest trend in studies of modern electronically and/or optically active materials is to provoke phase transformations induced by high electric fields or by short (femtosecond) powerful optical pulses. The systems of choice are cooperative electronic states whose broken symmetries give rise to topological defects. For typical quasi-one-dimensional architectures, those are the microscopic solitons taking from electrons the major roles as carriers of charge or spin. Because of the long-range ordering, the solitons experience unusual super-long-range forces leading to a sequence of phase transitions in their ensembles: the higher-temperature transition of the confinement and the lower one of aggregation into macroscopic walls. Here we present results of an extensive numerical modeling for ensembles of both neutral and charged solitons in both two- and three-dimensional systems. We suggest a specific Monte Carlo algorithm preserving the number of solitons, which substantially facilitates the calculations, allows to extend them to the three-dimensional case and to include the important long-range Coulomb interactions. The results confirm the first confinement transition, except for a very strong Coulomb repulsion, and demonstrate a pattern formation at the second transition of aggregation.
Lapidez, J. P. B.; Tablazon, J. P.; Lagmay, A. M. F. A.; Suarez, J. K. B.; Santiago, J. T.
2014-12-01
The Philippines is one of the countries most vulnerable to storm surge. It is located in the North-western Pacific basin which is the most active basin in the planet. An average of 20 tropical cyclones enters the Philippine area of responsibility (PAR) every year. The archipelagic nature of the country with regions having gently sloping coasts and shallow bays also contribute to the formation of extreme surges. Last November 2013, storm surge brought by super typhoon Haiyan severely damaged several coastal regions in the Visayan Islands. Haiyan left more than 6 300 casualties and damages amounting to more than $ 2 billion. Extreme storm surge events such as this highlight the need to establish a storm surge early warning system for the country. This study explores the development and evaluation of storm surge ensemble forecasting for the Philippines using the Japan Meteorological Agency (JMA) storm surge model. 36-hour, 24-hour, and 12-hour tropical cyclone forecasts are used to generate an ensemble storm surge forecast to give the most probable storm surge height at a specific point brought by an incoming tropical cyclone. The result of the storm surge forecast is compared to tide gauge record to evaluate the accuracy. The total time of computation and dissemination of forecast result is also examined to assess the feasibility of using the JMA storm surge model for operational purposes.
EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Shu, Qingya; Guo, Hanqi; Che, Limei; Yuan, Xiaoru; Liu, Junfeng; Liang, Jie
2016-04-19
We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based on ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.
Repeat-PPM Super-Symbol Synchronization
Connelly, J.
2016-11-01
To attain a wider range of data rates in pulse position modulation (PPM) schemes with constrained pulse durations, the sender can repeat a PPM symbol multiple times, forming a super-symbol. In addition to the slot and symbol synchronization typically required for PPM, the receiver must also properly align the noisy super-symbols. We present a low-complexity approximation of the maximum-likelihood method for performing super-symbol synchronization without use of synchronization sequences. We provide simulation results demonstrating performance advantage when PPM symbols are spread by a pseudo-noise sequence, as opposed to simply repeating. Additionally, the results suggest that this super-symbol synchronization technique requires signal levels below those required for reliable communication. This validates that the PPM spreading approach proposed to CCSDS can work properly as part of the overall scheme.
Axial Super-resolution Evanescent Wave Tomography
Pendharker, Sarang; Newman, Ward; Ogg, Stephen; Nazemifard, Neda; Jacob, Zubin
2016-01-01
Optical tomographic reconstruction of a 3D nanoscale specimen is hindered by the axial diffraction limit, which is 2-3 times worse than the focal plane resolution. We propose and experimentally demonstrate an axial super-resolution evanescent wave tomography (AxSET) method that enables the use of regular evanescent wave microscopes like Total Internal Reflection Fluorescence Microscope (TIRF) beyond surface imaging, and achieve tomographic reconstruction with axial super-resolution. Our proposed method based on Fourier reconstruction achieves axial super-resolution by extracting information from multiple sets of three-dimensional fluorescence images when the sample is illuminated by an evanescent wave. We propose a procedure to extract super-resolution features from the incremental penetration of an evanescent wave and support our theory by 1D (along the optical axis) and 3D simulations. We validate our claims by experimentally demonstrating tomographic reconstruction of microtubules in HeLa cells with an axi...
Mirror-enhanced super-resolution microscopy
2016-01-01
Axial excitation confinement beyond the diffraction limit is crucial to the development of next-generation, super-resolution microscopy. STimulated Emission Depletion (STED) nanoscopy offers lateral super-resolution using a donut-beam depletion, but its axial resolution is still over 500 nm. Total internal reflection fluorescence microscopy is widely used for single-molecule localization, but its ability to detect molecules is limited to within the evanescent field of ~ 100 nm from the cell a...
Ensemble data assimilation with an adjusted forecast spread
Directory of Open Access Journals (Sweden)
Sabrina Rainwater
2013-04-01
Full Text Available Ensemble data assimilation typically evolves an ensemble of model states whose spread is intended to represent the algorithm's uncertainty about the state of the physical system that produces the data. The analysis phase treats the forecast ensemble as a random sample from a background distribution, and it transforms the ensemble according to the background and observation error statistics to provide an appropriate sample for the next forecast phase. We find that in the presence of model nonlinearity and model error, it can be fruitful to rescale the ensemble spread prior to the forecast and then reverse this rescaling after the forecast. We call this approach forecast spread adjustment, which we discuss and test in this article using an ensemble Kalman filter and a 2005 model due to Lorenz. We argue that forecast spread adjustment provides a tunable parameter, that is, complementary to covariance inflation, which cumulatively increases ensemble spread to compensate for underestimation of uncertainty. We also show that as the adjustment parameter approaches zero, the filter approaches the extended Kalman filter if the ensemble size is sufficiently large. We find that varying the adjustment parameter can significantly reduce analysis and forecast errors in some cases. We evaluate how the improvement provided by forecast spread adjustment depends on ensemble size, observation error and model error. Our results indicate that the technique is most effective for small ensembles, small observation error and large model error, though the effectiveness depends significantly on the nature of the model error.
De praeceptis ferendis: good practice in multi-model ensembles
Directory of Open Access Journals (Sweden)
I. Kioutsioukis
2014-06-01
Full Text Available Ensembles of air quality models have been formally and empirically shown to outperform single models in many cases. Evidence suggests that ensemble error is reduced when the members form a diverse and accurate ensemble. Diversity and accuracy are hence two factors that should be taken care of while designing ensembles in order for them to provide better predictions. There exists a trade-off between diversity and accuracy for which one cannot be gained without expenses of the other. Theoretical aspects like the bias-variance-covariance decomposition and the accuracy-diversity decomposition are linked together and support the importance of creating ensemble that incorporates both the elements. Hence, the common practice of unconditional averaging of models without prior manipulation limits the advantages of ensemble averaging. We demonstrate the importance of ensemble accuracy and diversity through an inter-comparison of ensemble products for which a sound mathematical framework exists, and provide specific recommendations for model selection and weighting for multi model ensembles. To this end we have devised statistical tools that can be used for diagnostic evaluation of ensemble modelling products, complementing existing operational methods.
Energy Technology Data Exchange (ETDEWEB)
Feinberg, B.; Brown, I.G.
1986-06-01
A high current MEtal Vapor Vacuum Arc (MEVVA) ion source is to be installed in the third injector (Abel) at the SuperHILAC, representing the first accelerator use of this novel ion source. The MEVVA source has produced over 1 A of uranium in all charge states, with typically more than 100 electrical mA (emA) of U/sup 5 +/. A substantial fraction of this high current, heavy ion beam must be successfully transported to the entrance of the Wideroe linac to approach the 10 emA space-charge output limit of the Wideroe. Calculations show that up to 50 emA of U/sup 5 +/ can be transported through the present high voltage column. A bouncer will be added to the Cockcroft-Walton supply to handle the increased beam current. The Low Energy Beam Transport line vacuum will be improved to reduce charge exchange, and the phase matching between the 23 MHz Wideroe and the 70 MHz Alvarez linacs will be improved by the addition of two 70 HMz bunchers. The installation of the MEVVA source along with the modifications described above are expected to result in a five-fold increase in beam delivered to Bevatron experiments, increasing the extracted uranium beam to 5 x 10/sup 7/ ions/pulse.
Energy Technology Data Exchange (ETDEWEB)
Biagini, M.E.; Boni, R.; Boscolo, M.; Demma, T.; Drago, A.; Guiducci, S.; Raimondi, P.; Tomassini, S.; Zobov, M.; /Frascati; Bertsche, K.; Donald, M.; Nosochkov, Y.; Novokhatski, A.; Seeman, J.; Sullivan, M.; Yocky, G.; Wienands, U.; Wittmer, W.; /SLAC; Koop, I.; Levichev, E.; Nikitin, S.; /Novosibirsk, IYF /KEK, Tsukuba /Pisa U. /CERN
2010-08-26
The SuperB project aims at the construction of an asymmetric very high luminosity B-Factory on the Frascati/Tor Vergata (Italy) area, providing a uniquely sensitive probe of New Physics in the flavour sector of the Standard Model. The luminosity goal of 10{sup 36} cm{sup -2} s{sup -1} can be reached with a new collision scheme with 'large Piwinski angle' (LPA) and the use of 'crab waist sextupoles' (CW). A LPA&CW Interaction Region (IR) has been successfully tested at the DA{Phi}NE {Phi}-Factory at LNF-Frascati in 2008. The LPA&CW scheme, together with very low {beta}*, will allow for operation with relatively low beam currents and reasonable bunch length, comparable to those of PEP-II and KEKB. In the High Energy Ring (HER), two spin rotators will bring longitudinally polarized beams into collision at the IP. The lattice has been designed with a very low intrinsic emittance and is quite compact, less than 2 km long. The tight focusing requires the final doublet quadrupoles to be very close to the IP and very compact. A Conceptual Design Report was published in March 2007, and beam dynamics and collective effects R&D studies are in progress in order to publish a Technical Design Report by the end of 2010.
Energy Technology Data Exchange (ETDEWEB)
Biagini, M.E.; Raimondi, P.; /Frascati; Piminov, P.; Sinyatkin, S.; /Novosibirsk, IYF; Nosochkov, Y.; Wittmer, W.; /SLAC
2010-08-25
The SuperB asymmetric e{sup +}e{sup -} collider is designed for 10{sup 36} cm{sup -2} s{sup -1} luminosity and beam energies of 6.7 and 4.18 GeV for e{sup +} and e{sup -} respectively. The High and Low Energy Rings (HER and LER) have one Interaction Point (IP) with 66 mrad crossing angle. The 1258 m rings fit to the INFN-LNF site at Frascati. The ring emittance is minimized for the high luminosity. The Final Focus (FF) chromaticity correction is optimized for maximum transverse acceptance and energy bandwidth. Included Crab Waist sextupoles suppress betatron resonances induced in the collisions with a large Piwinski angle. The LER Spin Rotator sections provide longitudinally polarized electron beam at the IP. The lattice is flexible for tuning the machine parameters and compatible with reusing the PEP-II magnets, RF cavities and other components. Details of the lattice design are presented.
AUTHOR|(CDS)2156302
2016-01-01
The Super VELO is the Run 5 upgrade of the VeloPix detector of the LHCb experiment. Its most challenging task is to cope with a luminosity increase of the factor 10. This study examines the potential physics performance of a detector based on the VeloPix design at high luminosity conditions. It is found that an unmodified VeloPix detector shows poor performance when exposed to 10x design luminosity, most gravely high ghost rates of 40 %. When applying basic assumptions about material changes such as cutting the silicon thickness by half and removing the RF foil, the ghost rate drops by 20 %. When using thin silicon and re-optimizing the tracking algorithm, the ghost rate can even be reduced by 60 %. Applying the additional modification of a pixel area size four times smaller, the ghost rate drops by 88 % and the IP resolution improves. Finally, in a dream scenario with thin silicon, smaller pixels and no RF foil, big gains in resolution and a ghost rate of less than 4 % can be achieved.
Institute of Scientific and Technical Information of China (English)
ZHENG Fei; ZHU Jiang
2010-01-01
The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty.Therefore,the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system.Based on the multivariate empirical onhogonal function(MEOF)method,a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter(EnKF)data assimilation,with a reasonable consideration of the physical relationships between different model variables.The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations.The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations.The comparisons show that the model uncertainties prior to the first analysis time,which are forecasted from the balanced ensemble initial fields,maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields.The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information.Also,a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles,while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly.
Seasonal hydrological ensemble forecasts over Europe
Arnal, Louise; Wetterhall, Fredrik; Pappenberger, Florian
2015-04-01
Seasonal forecasts have an important socio-economic value in hydro-meteorological forecasting. The applications are for example hydropower management, spring flood prediction and water resources management. The latter includes prediction of low flows, primordial for navigation, water quality assessment, droughts and agricultural water needs. Traditionally, seasonal hydrological forecasts are done using the observed discharge from previous years, so called Ensemble Streamflow Prediction (ESP). With the recent increasing development of seasonal meteorological forecasts, the incentive for developing and improving seasonal hydrological forecasts is great. In this study, a seasonal hydrological forecast, driven by the ECMWF's System 4 (SEA), was compared with an ESP of modelled discharge using observations. The hydrological model used for both forecasts was the LISFLOOD model, run over a European domain with a spatial resolution of 5 km. The forecasts were produced from 1990 until the present time, with a daily time step. They were issued once a month with a lead time of seven months. The SEA forecasts are constituted of 15 ensemble members, extended to 51 members every three months. The ESP forecasts comprise 20 ensembles and served as a benchmark for this comparative study. The forecast systems were compared using a diverse set of verification metrics, such as continuous ranked probability scores, ROC curves, anomaly correlation coefficients and Nash-Sutcliffe efficiency coefficients. These metrics were computed over several time-scales, ranging from a weekly to a six-months basis, for each season. The evaluation enabled the investigation of several aspects of seasonal forecasting, such as limits of predictability, timing of high and low flows, as well as exceedance of percentiles. The analysis aimed at exploring the spatial distribution and timely evolution of the limits of predictability.
Seasonal hydrological ensemble forecasts over Europe
Arnal, Louise; Wetterhall, Fredrik; Stephens, Elisabeth; Cloke, Hannah; Pappenberger, Florian
2016-04-01
This study investigates the limits of predictability in dynamical seasonal discharge forecasting, in both space and time, over Europe. Seasonal forecasts have an important socioeconomic value. Applications are numerous and cover hydropower management, spring flood prediction, low flow prediction for navigation and agricultural water demands. Additionally, the constant increase in NWP skill for longer lead times and the predicted increase in the intensity and frequency of hydro-meteorological extremes, have amplified the incentive to promote and further improve hydrological forecasts on sub-seasonal to seasonal timescales. In this study, seasonal hydrological forecasts (SEA), driven by the ECMWF's System 4 in hindcast mode, were analysed against an Ensemble Streamflow Prediction (ESP) benchmark. The ESP was forced with an ensemble of resampled historical meteorological observations and started with perfect initial conditions. Both forecasts were produced by the LISFLOOD model, run on the pan-European scale with a spatial resolution of 5 by 5 km. The forecasts were issued monthly on a daily time step, from 1990 until the current time, up to a lead time of 7 months. The seasonal discharge forecasts were analysed against the ESP on a catchment scale in terms of their accuracy, skill and sharpness, using a diverse set of verification metrics (e.g. KGE, CRPSS and ROC). Additionally, a reverse-ESP was constructed by forcing the LISFLOOD model with a single perfect meteorological set of observations and initiated from an ensemble of resampled historical initial conditions. The comparison of the ESP with the reverse-ESP approach enabled the identification of the respective contribution of meteorological forcings and hydrologic initial conditions errors to seasonal discharge forecasting uncertainties in Europe. These results could help pinpoint target elements of the forecasting chain which, after being improved, could lead to substantial increase in discharge predictability
A Framework for Non-Equilibrium Statistical Ensemble Theory
Institute of Scientific and Technical Information of China (English)
BI Qiao; HE Zu-Tan; LIU Jie
2011-01-01
Since Gibbs synthesized a general equilibrium statistical ensemble theory, many theorists have attempted to generalized the Gibbsian theory to non-equilibrium phenomena domain, however the status of the theory of nonequilibrium phenomena can not be said as firm as well established as the Gibbsian ensemble theory. In this work, we present a framework for the non-equilibrium statistical ensemble formalism based on a subdynamic kinetic equation (SKE) rooted from the Brussels-Austin school and followed by some up-to-date works. The constructed key is to use a similarity transformation between Gibbsian ensembles formalism based on Liouville equation and the subdynamic ensemble formalism based on the SKE. Using this formalism, we study the spin-Boson system, as cases of weak coupling or strongly coupling, and obtain the reduced density operators for the Canonical ensembles easily.
Cluster ensembles, quantization and the dilogarithm
DEFF Research Database (Denmark)
Fock, Vladimir; Goncharov, Alexander B.
2009-01-01
, possibly degenerate, and the space has a Poisson structure. The map is compatible with these structures. The dilogarithm together with its motivic and quantum avatars plays a central role in the cluster ensemble structure. We define a non-commutative -deformation of the -space. When is a root of unity...... group . It is an algebraic-geometric avatar of higher Teichmüller theory on related to . We suggest that there exists a duality between the and spaces. In particular, we conjecture that the tropical points of one of the spaces parametrise a basis in the space of functions on the Langlands dual space. We...
Accurate Atom Counting in Mesoscopic Ensembles
Hume, D B; Joos, M; Muessel, W; Strobel, H; Oberthaler, M K
2013-01-01
Many cold atom experiments rely on precise atom number detection, especially in the context of quantum-enhanced metrology where effects at the single particle level are important. Here, we investigate the limits of atom number counting via resonant fluorescence detection for mesoscopic samples of trapped atoms. We characterize the precision of these fluorescence measurements beginning from the single-atom level up to more than one thousand. By investigating the primary noise sources, we obtain single-atom resolution for atom numbers as high as 1200. This capability is an essential prerequisite for future experiments with highly entangled states of mesoscopic atomic ensembles.
Accurate Atom Counting in Mesoscopic Ensembles
Hume, D. B.; Stroescu, I.; Joos, M.; Muessel, W.; Strobel, H.; Oberthaler, M. K.
2013-12-01
Many cold atom experiments rely on precise atom number detection, especially in the context of quantum-enhanced metrology where effects at the single particle level are important. Here, we investigate the limits of atom number counting via resonant fluorescence detection for mesoscopic samples of trapped atoms. We characterize the precision of these fluorescence measurements beginning from the single-atom level up to more than one thousand. By investigating the primary noise sources, we obtain single-atom resolution for atom numbers as high as 1200. This capability is an essential prerequisite for future experiments with highly entangled states of mesoscopic atomic ensembles.
Supervised Ensemble Classification of Kepler Variable Stars
Bass, Gideon
2016-01-01
Variable star analysis and classification is an important task in the understanding of stellar features and processes. While historically classifications have been done manually by highly skilled experts, the recent and rapid expansion in the quantity and quality of data has demanded new techniques, most notably automatic classification through supervised machine learning. We present an expansion of existing work on the field by analyzing variable stars in the {\\em Kepler} field using an ensemble approach, combining multiple characterization and classification techniques to produce improved classification rates. Classifications for each of the roughly 150,000 stars observed by {\\em Kepler} are produced separating the stars into one of 14 variable star classes.
Modeling Coordination Problems in a Music Ensemble
DEFF Research Database (Denmark)
Frimodt-Møller, Søren R.
2008-01-01
This paper considers in general terms, how musicians are able to coordinate through rational choices in a situation of (temporary) doubt in an ensemble performance. A fictitious example involving a 5-bar development in an unknown piece of music is analyzed in terms of epistemic logic, more...... specifically a multi-agent system, where it is shown that perfect coordination can only be certain to take place if the musicians have common knowledge of certain rules of the composition. We subsequently argue, however, that the musicians need not agree on the central features of the piece of music in order...
Asymptotic expansions for the Gaussian unitary ensemble
DEFF Research Database (Denmark)
Haagerup, Uffe; Thorbjørnsen, Steen
2012-01-01
Let g : R ¿ C be a C8-function with all derivatives bounded and let trn denote the normalized trace on the n × n matrices. In Ref. 3 Ercolani and McLaughlin established asymptotic expansions of the mean value ¿{trn(g(Xn))} for a rather general class of random matrices Xn, including the Gaussian...... Unitary Ensemble (GUE). Using an analytical approach, we provide in the present paper an alternative proof of this asymptotic expansion in the GUE case. Specifically we derive for a random matrix Xn that where k is an arbitrary positive integer. Considered as mappings of g, we determine the coefficients...
Accurate atom counting in mesoscopic ensembles.
Hume, D B; Stroescu, I; Joos, M; Muessel, W; Strobel, H; Oberthaler, M K
2013-12-20
Many cold atom experiments rely on precise atom number detection, especially in the context of quantum-enhanced metrology where effects at the single particle level are important. Here, we investigate the limits of atom number counting via resonant fluorescence detection for mesoscopic samples of trapped atoms. We characterize the precision of these fluorescence measurements beginning from the single-atom level up to more than one thousand. By investigating the primary noise sources, we obtain single-atom resolution for atom numbers as high as 1200. This capability is an essential prerequisite for future experiments with highly entangled states of mesoscopic atomic ensembles.
Super-multiplex vibrational imaging
Wei, Lu; Chen, Zhixing; Shi, Lixue; Long, Rong; Anzalone, Andrew V.; Zhang, Luyuan; Hu, Fanghao; Yuste, Rafael; Cornish, Virginia W.; Min, Wei
2017-04-01
potential of this 24-colour (super-multiplex) optical imaging approach for elucidating intricate interactions in complex biological systems.
Validation of the Air Force Weather Agency Ensemble Prediction Systems
2014-03-27
to deterministic models. Results from ensemble weather input into operational risk management ( ORM ) destruction of enemy air defense simulations...growth during the analysis period (Toth and Kalnay, 1993; Toth and Kalnay, 1997). From this framework the ensemble transform bred vector, ensemble...features. Each of its 10 members is run independently using different configurations in the framework of the Weather Research and Forecasting (WRF
Unconditional two-mode squeezing of separated atomic ensembles
Parkins, A S; Solano, E
2005-01-01
We propose schemes for the unconditional preparation of a two-mode squeezed state of effective bosonic modes realized in a pair of atomic ensembles interacting collectively with optical cavity and laser fields. The scheme uses Raman transitions between stable atomic ground states and under ideal conditions produces pure entangled states in the steady state. The scheme works both for ensembles confined within a single cavity and for ensembles confined in separate, cascaded cavities.
The Moment Convergence Rates for Largest Eigenvalues of β Ensembles
Institute of Scientific and Technical Information of China (English)
Jun Shan XIE
2013-01-01
The paper focuses on the largest eigenvalues of the β-Hermite ensemble and theβ-Laguerre ensemble.In particular,we obtain the precise moment convergence rates of their largest eigenvalues.The results are motivated by the complete convergence for partial sums of i.i.d.random variables,and the proofs depend on the small deviations for largest eigenvalues of the β ensembles and tail inequalities of the general β Tracy-Widom law.
Extracting Value from Ensembles for Cloud-Free Forecasting
2011-09-01
for Medium range Weather Forecasting EMean Ensemble mean ETR Ensemble transform with rescaling EUMETSAT European Organization for the...transform method (ET) with rescaling ( ETR ) to define the initial atmospheric uncertainty (Wei et al. 2008). Adapted from the ET method devised by...variances of each grid point to further restrain the initial ensemble spread. The ETR method replaced the breeding method in GEFS during NCEP’s May
On sequential observation processing in localized ensemble Kalman filters
Nerger, Lars
2014-01-01
The different variants of current ensemble square-root Kalman filters assimilate either all observations at once or perform a sequence in which batches of observations or each single observation is assimilated. The sequential observation processing is used in filter algorithms like the ensemble adjustment Kalman filter (EAKF) and the ensemble square-root filter (EnSRF) and can result in computationally efficient algorithms because matrix inversions in the observation space are reduced to the ...
Energy Technology Data Exchange (ETDEWEB)
Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA
2016-10-01
The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.
Ensemble-based forecasting at Horns Rev: Ensemble conversion and kernel dressing
DEFF Research Database (Denmark)
Pinson, Pierre; Madsen, Henrik
. The obtained ensemble forecasts of wind power are then converted into predictive distributions with an original adaptive kernel dressing method. The shape of the kernels is driven by a mean-variance model, the parameters of which are recursively estimated in order to maximize the overall skill of obtained...
2011-09-01
variable is appropriately sized for the region ( UCAR 2010). 4. An Isotropic Joint-Ensemble Majumdar and Finochio (2010) develop a probability circle...Forecasting, 22, 671–675. UCAR , cited 2010: NCEP Perturbation Method. [Available online at http://www.meted.ucar.edu/nwp/pcu2/ens_matrix
The MIP Ensemble Simulation: Local Ensemble Statistics in the Cosmic Web
Aragon-Calvo, M A
2012-01-01
Here we present a novel N-body simulation technique that allows us to compute ensemble statistics on a local basis, directly relating halo properties to their environment. This is achieved by the use of an ensemble simulation in which the otherwise independent realizations share the same fluctuations above a given cut-off scale. This produces a constrained ensemble where the LSS is common to all realizations while having an independent halo population. By generating a large number of semi-independent realizations we can effectively increase the local halo density by an arbitrary factor thus breaking the fundamental limit of the finite halo density (for a given halo mass range) determined by the halo mass function. This technique allows us to compute local ensemble statistics of the matter/halo distribution at a particular position in space, removing the intrinsic stochasticity in the halo formation process and directly relating halo properties to their environment. This is a major improvement over global desc...
Deformed Gaussian Orthogonal Ensemble Analysis of the Interacting Boson Model
Pato, M P; Lima, C L; Hussein, M S; Alhassid, Y
1994-01-01
A Deformed Gaussian Orthogonal Ensemble (DGOE) which interpolates between the Gaussian Orthogonal Ensemble and a Poissonian Ensemble is constructed. This new ensemble is then applied to the analysis of the chaotic properties of the low lying collective states of nuclei described by the Interacting Boson Model (IBM). This model undergoes a transition order-chaos-order from the $SU(3)$ limit to the $O(6)$ limit. Our analysis shows that the quantum fluctuations of the IBM Hamiltonian, both of the spectrum and the eigenvectors, follow the expected behaviour predicted by the DGOE when one goes from one limit to the other.
Bayesian ensemble refinement by replica simulations and reweighting.
Hummer, Gerhard; Köfinger, Jürgen
2015-12-28
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.
Adiabatic Passage of Collective Excitations in Atomic Ensembles
Institute of Scientific and Technical Information of China (English)
LIYong; MIAOYuan-Xiu; SUNChang-Pu
2004-01-01
We describe a theoretical scheme that allows for transfer of quantum states of atomic collective excitation between two macroscopic atomic ensembles localized in two spatially-separated domains. The conception is based on the occurrence of double-exciton dark states due to the collective destructive quantum interference of the emissions from the two atomic ensembles. With an adiabatically coherence manipulation for the atom-field couplings by stimulated Rmann scattering, the dark states will extrapolate from an exciton state of an ensemble to that of another. This realizes the transport of quantum information among atomic ensembles.
Adiabatic Passage of Collective Excitations in Atomic Ensembles
Institute of Scientific and Technical Information of China (English)
LI Yong; MIAO Yuan-Xiu; SUN Chang-Pu
2004-01-01
We describe a theoretical scheme that allows for transfer of quantum states of atomic collective excitation between two macroscopic atomic ensembles localized in two spatially-separated domains. The conception is based on the occurrence of double-exciton dark states due to the collective destructive quantum interference of the emissions from the two atomic ensembles. With an adiabatically coherence manipulation for the atom-field couplings by stimulated Ramann scattering, the dark states will extrapolate from an exciton state of an ensemble to that of another. This realizes the transport of quantum information among atomic ensembles.
Relation between native ensembles and experimental structures of proteins
DEFF Research Database (Denmark)
Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.
2006-01-01
Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest...
Fractional exclusion statistics and the Random Matrix Boson Ensemble
Hernández-Quiroz, Saul; Benet, Luis; Flores, Jorge; Cocho, Germinal
2012-01-01
The k-body Gaussian Embedded Ensemble of Random Matrices is considered for N bosons distributed on two single-particle levels. When k = N, the ensemble is equivalent to the Gaussian Orthogonal Ensemble (GOE), and when k = 2 it corresponds to the Two-body Random Ensemble (TBRE) for bosons. It is shown that the energy spectrum leads to a rank function which is of the form of a discrete generalized beta distribution. The same distribution is obtained assuming N non-interacting quasiparticles that obey the fractional exclusion statistics introduced by Haldane two decades ago.
Cluster Ensemble-based Image Segmentation
Directory of Open Access Journals (Sweden)
Xiaoru Wang
2013-07-01
Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new\tcluster ensemble-based image\tsegmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.
Online cross-validation-based ensemble learning.
Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark
2017-05-04
Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Nanobiosensing with Arrays and Ensembles of Nanoelectrodes
Directory of Open Access Journals (Sweden)
Najmeh Karimian
2016-12-01
Full Text Available Since the first reports dating back to the mid-1990s, ensembles and arrays of nanoelectrodes (NEEs and NEAs, respectively have gained an important role as advanced electroanalytical tools thank to their unique characteristics which include, among others, dramatically improved signal/noise ratios, enhanced mass transport and suitability for extreme miniaturization. From the year 2000 onward, these properties have been exploited to develop electrochemical biosensors in which the surfaces of NEEs/NEAs have been functionalized with biorecognition layers using immobilization modes able to take the maximum advantage from the special morphology and composite nature of their surface. This paper presents an updated overview of this field. It consists of two parts. In the first, we discuss nanofabrication methods and the principles of functioning of NEEs/NEAs, focusing, in particular, on those features which are important for the development of highly sensitive and miniaturized biosensors. In the second part, we review literature references dealing the bioanalytical and biosensing applications of sensors based on biofunctionalized arrays/ensembles of nanoelectrodes, focusing our attention on the most recent advances, published in the last five years. The goal of this review is both to furnish fundamental knowledge to researchers starting their activity in this field and provide critical information on recent achievements which can stimulate new ideas for future developments to experienced scientists.
Hsaing Waing: Classical Ensemble of Myanmar
Directory of Open Access Journals (Sweden)
Chalermkit Kengkeaw
2013-09-01
Full Text Available Hsaing Waing is a classical music ensemble and a prominent culturalidentity of Myanmar. The Hsaing Waing ensemble consists of many instruments such as the Pat Waing, Muang Hsaing, Hne, Chauk Lon Bat, Byaung, Wa, Wallet Kok, Yakin, Si, and Mong. The earliest historical record of the Hsaing Waing is in 1544 where the Pat Waing and possibly the Hsaing Waing, was in royal service at the court of King Tabinshwehti of the Taungoo dynasty and prospered under the Kaunbaun dynasty up to colonial rule. During colonization, Hsaing Waing’s popularity declined but other innovations were introduced such as modern recording mediums and broadcasts which transferred the popularity of Hsaing Waing to a broader public audience and brought innovation to religious music, ceremonial rituals, fusion of westernmusical instruments such as the piano, violin and mandolin. The wealth of knowledge and numbers of connoisseur during the Kaunbaun dynasty led to the transfer of knowledge to many apprentices which were responsible for the development and adaptation and continuation of Hsaing Waing during colonization, socialism and independence. The transfer of knowledge was carried out by previous generations through apprentices, family members, close relatives and inspired individuals. The factors for the successful inheritance of Hsaing Waing are management, education, musicians and opportunity.
Ensemble Kalman filtering with residual nudging
Directory of Open Access Journals (Sweden)
Xiaodong Luo
2012-10-01
Full Text Available Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF by (in effect adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.
Deterministic Mean-Field Ensemble Kalman Filtering
Law, Kody J. H.
2016-05-03
The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.
Ensemble Kalman filtering with residual nudging
Luo, X.
2012-10-03
Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.
Axial super-resolution evanescent wave tomography.
Pendharker, Sarang; Shende, Swapnali; Newman, Ward; Ogg, Stephen; Nazemifard, Neda; Jacob, Zubin
2016-12-01
Optical tomographic reconstruction of a three-dimensional (3D) nanoscale specimen is hindered by the axial diffraction limit, which is 2-3 times worse than the focal plane resolution. We propose and experimentally demonstrate an axial super-resolution evanescent wave tomography method that enables the use of regular evanescent wave microscopes like the total internal reflection fluorescence microscope beyond surface imaging and achieve a tomographic reconstruction with axial super-resolution. Our proposed method based on Fourier reconstruction achieves axial super-resolution by extracting information from multiple sets of 3D fluorescence images when the sample is illuminated by an evanescent wave. We propose a procedure to extract super-resolution features from the incremental penetration of an evanescent wave and support our theory by one-dimensional (along the optical axis) and 3D simulations. We validate our claims by experimentally demonstrating tomographic reconstruction of microtubules in HeLa cells with an axial resolution of ∼130 nm. Our method does not require any additional optical components or sample preparation. The proposed method can be combined with focal plane super-resolution techniques like stochastic optical reconstruction microscopy and can also be adapted for THz and microwave near-field tomography.
Axial super-resolution evanescent wave tomography
Pendharker, Sarang; Shende, Swapnali; Newman, Ward; Ogg, Stephen; Nazemifard, Neda; Jacob, Zubin
2016-12-01
Optical tomographic reconstruction of a 3D nanoscale specimen is hindered by the axial diffraction limit, which is 2-3 times worse than the focal plane resolution. We propose and experimentally demonstrate an axial super-resolution evanescent wave tomography (AxSET) method that enables the use of regular evanescent wave microscopes like Total Internal Reflection Fluorescence Microscope (TIRF) beyond surface imaging, and achieve tomographic reconstruction with axial super-resolution. Our proposed method based on Fourier reconstruction achieves axial super-resolution by extracting information from multiple sets of three-dimensional fluorescence images when the sample is illuminated by an evanescent wave. We propose a procedure to extract super-resolution features from the incremental penetration of an evanescent wave and support our theory by 1D (along the optical axis) and 3D simulations. We validate our claims by experimentally demonstrating tomographic reconstruction of microtubules in HeLa cells with an axial resolution of $\\sim$130 nm. Our method does not require any additional optical components or sample preparation. The proposed method can be combined with focal plane super-resolution techniques like STORM and can also be adapted for THz and microwave near-field tomography.
Institute of Scientific and Technical Information of China (English)
Jun Kyung KAY; Hyun Mee KIM; Young-Youn PARK; Joohyung SON
2013-01-01
Using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) implemented at the Korea Meteorological Administration (KMA),the effect of doubling the ensemble size on the performance of ensemble prediction in the warm season was evaluated.Because a finite ensemble size causes sampling error in the full forecast probability distribution function (PDF),ensemble size is closely related to the efficiency of the ensemble prediction system.Prediction capability according to doubling the ensemble size was evaluated by increasing the number of ensembles from 24 to 48 in MOGREPS implemented at the KMA.The initial analysis perturbations generated by the Ensemble Transform Kalman Filter (ETKF) were integrated for 10 days from 22 May to 23 June 2009.Several statistical verification scores were used to measure the accuracy,reliability,and resolution of ensemble probabilistic forecasts for 24 and 48 ensemble member forecasts.Even though the results were not significant,the accuracy of ensemble prediction improved slightly as ensemble size increased,especially for longer forecast times in the Northern Hemisphere.While increasing the number of ensemble members resulted in a slight improvement in resolution as forecast time increased,inconsistent results were obtained for the scores assessing the reliability of ensemble prediction.The overall performance of ensemble prediction in terms of accuracy,resolution,and reliability increased slightly with ensemble size,especially for longer forecast times.
Energy Technology Data Exchange (ETDEWEB)
Kenyon, Scott J. [Smithsonian Astrophysical Observatory, 60 Garden Street, Cambridge, MA 02138 (United States); Bromley, Benjamin C., E-mail: skenyon@cfa.harvard.edu, E-mail: bromley@physics.utah.edu [Department of Physics, University of Utah, 201 JFB, Salt Lake City, UT 84112 (United States)
2014-01-01
We investigate formation mechanisms for icy super-Earth-mass planets orbiting at 2-20 AU around 0.1-0.5 M {sub ☉} stars. A large ensemble of coagulation calculations demonstrates a new formation channel: disks composed of large planetesimals with radii of 30-300 km form super-Earths on timescales of ∼1 Gyr. In other gas-poor disks, a collisional cascade grinds planetesimals to dust before the largest planets reach super-Earth masses. Once icy Earth-mass planets form, they migrate through the leftover swarm of planetesimals at rates of 0.01-1 AU Myr{sup –1}. On timescales of 10 Myr to 1 Gyr, many of these planets migrate through the disk of leftover planetesimals from semimajor axes of 5-10 AU to 1-2 AU. A few percent of super-Earths might migrate to semimajor axes of 0.1-0.2 AU. When the disk has an initial mass comparable with the minimum-mass solar nebula, scaled to the mass of the central star, the predicted frequency of super-Earths matches the observed frequency.
Assessing resolution in super-resolution imaging.
Demmerle, Justin; Wegel, Eva; Schermelleh, Lothar; Dobbie, Ian M
2015-10-15
Resolution is a central concept in all imaging fields, and particularly in optical microscopy, but it can be easily misinterpreted. The mathematical definition of optical resolution was codified by Abbe, and practically defined by the Rayleigh Criterion in the late 19th century. The limit of conventional resolution was also achieved in this period, and it was thought that fundamental constraints of physics prevented further increases in resolution. With the recent development of a range of super-resolution techniques, it is necessary to revisit the concept of optical resolution. Fundamental differences in super-resolution modalities mean that resolution is not a directly transferrable metric between techniques. This article considers the issues in resolution raised by these new technologies, and presents approaches for comparing resolution between different super-resolution methods.
Architectural Engineering to Super-Light Structures
DEFF Research Database (Denmark)
Castberg, Niels Andreas
with architectural engineering as a starting point. The thesis is based on a two stringed hypothesis: Architectural engineering gives rise to better architecture and Super-Light Structures support and enables a static, challenging architecture. The aim of the thesis is to clarify architectural engineering's impact...... on the work process between architects and engineers in the design development. Using architectural engineering, Super-Light Structures are examined in an architectural context, and it is explained how digital tools can support architectural engineering and design of Super-Light Structures. The experiences...... to be subjects of examination for this thesis. The research results show that architectural engineering has a significant impact on a design process. The projects illustrate that simple explanations, underpinned by visualisations of the challenges between shape versus structure, often creates a shared...
Volume and structural analysis of super-cooled water under high pressure
Duki, Solomon F.; Tsige, Mesfin
2012-02-01
Motivated by recent experimental study of super-cooled water at high pressure [1], we performed atomistic molecular dynamic simulations study on bulk water molecules at isothermal-isobaric ensemble. These simulations are performed at temperatures that range from 40 K to 380 K using two different cooling rates, 10K/ns and 10K/5ns, and pressure that ranges from 1atm to 10000 atm. Our analysis for the variation of the volume of the bulk sample against temperature indicates a downward concave shape for pressures above certain values, as reported in [1]. The same downward concave behavior is observed at high pressure on the mean-squared-displacements (MSD) of the water molecules when the MSD is plotted against time. To get further insight on the effect of the pressure on the sample we have also performed a structural analysis of the sample.[4pt] [1] O. Mishima, J. Chem. Phys. 133, 144503 (2010);
Detection of a low-eccentricity and super-massive planet to the subgiant HD 38801
Harakawa, Hiroki; Fischer, Debra A; Ida, Shigeru; Omiya, Masashi; Johnson, John A; Marcy, Geoffrey W; Toyota, Eri; Hori, Yasunori; Howard, Andrew W
2010-01-01
We report the detection of a large mass planet orbiting around the K0 metal-rich subgiant HD38801 ($V=8.26$) by precise radial velocity (RV) measurements from the Subaru Telescope and the Keck Telescope. The star has a mass of $1.36M_{\\odot}$ and metallicity of [Fe/H]= +0.26. The RV variations are consistent with a circular orbit with a period of 696.0 days and a velocity semiamplitude of 200.0\\mps, which yield a minimum-mass for the companion of $10.7\\mjup$ and semimajor axis of 1.71 AU. Such super-massive objects with very low-eccentricities and hundreds of days period are uncommon among the ensemble of known exoplanets.
Breeding Super-Earths and Birthing Super-Puffs in Transitional Disks
Lee, Eve J
2015-01-01
The riddle posed by super-Earths (1-4$R_\\oplus$, 2-20$M_\\oplus$) is that they are not Jupiters: their core masses are large enough to trigger runaway gas accretion, yet somehow super-Earths accreted atmospheres that weigh only a few percent of their total mass. We show that this puzzle is solved if super-Earths formed late, as the last vestiges of their parent gas disks were about to clear. This scenario would seem to present fine-tuning problems, but we show that there are none. Ambient gas densities can span many (up to 9) orders of magnitude, and super-Earths can still robustly emerge after $\\sim$0.1-1 Myr with percent-by-weight atmospheres. Super-Earth cores are naturally bred in gas-poor environments where gas dynamical friction has weakened sufficiently to allow constituent protocores to merge. So little gas is present at the time of core assembly that cores hardly migrate by disk torques: formation of super-Earths can be in situ. The picture --- that close-in super-Earths form in a gas-poor (but not ga...
KML Super Overlay to WMS Translator
Plesea, Lucian
2007-01-01
This translator is a server-based application that automatically generates KML super overlay configuration files required by Google Earth for map data access via the Open Geospatial Consortium WMS (Web Map Service) standard. The translator uses a set of URL parameters that mirror the WMS parameters as much as possible, and it also can generate a super overlay subdivision of any given area that is only loaded when needed, enabling very large areas of coverage at very high resolutions. It can make almost any dataset available as a WMS service visible and usable in any KML application, without the need to reformat the data.
Super-resolution optical microscopy: multiple choices.
Huang, Bo
2010-02-01
The recent invention of super-resolution optical microscopy enables the visualization of fine features in biological samples with unprecedented clarity. It creates numerous opportunities in biology because vast amount of previously obscured subcellular processes now can be directly observed. Rapid development in this field in the past two years offers many imaging modalities that address different needs but they also complicates the choice of the 'perfect' method for answering a specific question. Here I will briefly describe the principles of super-resolution optical microscopy techniques and then focus on comparing their characteristics in various aspects of practical applications.
Super resolution of images and video
Katsaggelos, Aggelos K
2007-01-01
This book focuses on the super resolution of images and video. The authors' use of the term super resolution (SR) is used to describe the process of obtaining a high resolution (HR) image, or a sequence of HR images, from a set of low resolution (LR) observations. This process has also been referred to in the literature as resolution enhancement (RE). SR has been applied primarily to spatial and temporal RE, but also to hyperspectral image enhancement. This book concentrates on motion based spatial RE, although the authors also describe motion free and hyperspectral image SR problems. Also exa
Super-Laplacians and their symmetries
Howe, P. S.; Lindström, U.
2017-05-01
A super-Laplacian is a set of differential operators in superspace whose highestdimensional component is given by the spacetime Laplacian. Symmetries of super-Laplacians are given by linear differential operators of arbitrary finite degree and are determined by superconformal Killing tensors. We investigate these in flat superspaces. The differential operators determining the symmetries give rise to algebras which can be identified in many cases with the tensor algebras of the relevant superconformal Lie algebras modulo certain ideals. They have applications to Higher Spin theories.
New method for making super-plastic glasses
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
@@ It was a long-cherished dream for materials scientists to find a nearly ideal metallic alloy with high strength and super-plasticity concurrently as a super-material both extremely strong and exceptionally hard for human use.
Second invariant for two-dimensional classical super systems
Indian Academy of Sciences (India)
S C Mishra; Roshan Lal; Veena Mishra
2003-10-01
Construction of superpotentials for two-dimensional classical super systems (for ≥ 2) is carried out. Some interesting potentials have been studied in their super form and also their integrability.
Thermal Insulation Distribution Pattern of Layered Clothing Ensemble
Institute of Scientific and Technical Information of China (English)
李俊; 韦鸿发; 刘岩; 张渭源
2004-01-01
With a thermal manikin, the distribution pattern of thermal insulation in multi-layered clothing ensemble is studied. It is found that the thermal insulation of multi-layered clothing ensemble has certain statistical relationship with the thermal insulation of each layer, and the prediction equation has been established.
Building Identity in Collegiate Midlevel Choral Ensembles: The Director's Perspective
Major, Marci L.
2017-01-01
This study was designed to explore the director's perspective on the role organizational images play in social identity development in midlevel choral ensembles. Using a phenomenological methodology, I interviewed 10 current or former directors of midlevel choral ensembles from eight midwestern U.S. colleges and universities. Directors cited…
Calculation of the chemical potential in the Gibbs ensemble
Smit, B.; Frenkel, D.
1989-01-01
An expression for the chemical potential in the Gibbs ensemble is derived. For finite system sizes this expression for the chemical potential differs system-atically from Widom's test particle insertion method for the N, V, T ensemble. In order to compare these two methods for calculating the chemic
Stochastic and dynamical downscaling of ensemble precipitation forecasts
Brussolo, E.; von Hardenberg, J.; Rebora, N.
2009-04-01
Forecasting hydrogeological risk in small basins requires quantitative forecasts and an estimate of the probability of occurrence of severe, localized precipitation events at spatial scales of the order of tens of kilometers or less, significantly smaller than those currently provided by large scale, global, ensemble forecasting systems (EPS). Dynamically based forecasts at these scales can be obtained extending EPS scenarios with high-resolution, non-hydrostatic, limited area ensemble prediction systems. An alternative is represented by the direct application of stochastic downscaling techniques to the large scale ensemble forecasts. This work compares the performances of these two very different ensemble forecast downscaling approaches. To this purpose we consider ensemble forecasts provided by the ECMWF EPS, downscaled in space using the RainFARM stochastic technique [1], and ensembles of forecasts obtained from the COSMO-LEPS limited area prediction system (which also uses ECMWF EPS ensemble members as boundary conditions), for three intense precipitation events over northern Italy in 2006. The statistical properties of the fields produced with these two techniques are compared and the skill of the resulting ensembles is verified against direct precipitation measurements from a dense network of rain gauges. Reference: 1. Rebora, N., L. Ferraris, J. von Hardenberg, and A. Provenzale, 2006: The RainFARM: Rainfall Downscaling by a Filtered AutoRegressive Model. J. Hydrometeorol., 7, 724-738.
A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation
Altaf, Muhammad
2014-08-01
This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.
Ensemble Bayesian model averaging using Markov Chain Monte Carlo sampling
Vrugt, J.A.; Diks, C.G.H.; Clark, M.
2008-01-01
Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In t
Conductor and Ensemble Performance Expressivity and State Festival Ratings
Price, Harry E.; Chang, E. Christina
2005-01-01
This study is the second in a series examining the relationship between conducting and ensemble performance. The purpose was to further examine the associations among conductor, ensemble performance expressivity, and festival ratings. Participants were asked to rate the expressivity of video-only conducting and parallel audio-only excerpts from a…
Ensembles and their modules as objects of cartosemiotic inquiry
Directory of Open Access Journals (Sweden)
Hansgeorg Schlichtmann
2010-01-01
Full Text Available The structured set of signs in a map face -- here called map-face aggregate or MFA -- and the associated marginal notes make up an ensemble of modules or components (modular ensemble. Such ensembles are recognized where groups of entries are intuitively viewed as complex units, which includes the case that entries are consulted jointly and thus are involved in the same process of sign reception. Modular ensembles are amenable to semiotic study, just as are written or pictorial stories. Four kinds (one of them mentioned above are discussed in detail, two involving single MFAs, the other two being assemblages of maps, such as atlases. In terms of their internal structure, two types are recognized: the combinate (or grouping, in which modules are directly linked by combinatorial relations (example above, and the cumulate (or collection (of documents, in which modules are indirectly related through some conceptual commonality (example: series of geological maps. The discussion then turns to basic points concerning modular ensembles (identification of a module, internal organization of an ensemble, and characteristics which establish an ensemble as a unit and further to a few general semiotic concepts as they relate to the present research. Since this paper originated as a reaction to several of A. Wolodtschenko’s recent publications, it concludes with comments on some of his arguments which pertain to modular ensembles.
An iterative ensemble Kalman filter for reservoir engineering applications
Krymskaya, M.V.; Hanea, R.G.; Verlaan, M.
2009-01-01
The study has been focused on examining the usage and the applicability of ensemble Kalman filtering techniques to the history matching procedures. The ensemble Kalman filter (EnKF) is often applied nowadays to solving such a problem. Meanwhile, traditional EnKF requires assumption of the
Ensemble Forecast: A New Approach to Uncertainty and Predictability
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990s in numerical centers around the world due to the increase in computation ability. One of the main purposes of numerical ensemble forecasts is to try to assimilate the initial uncertainty (initial error) and the forecast uncertainty (forecast error) by applying either the initial perturbation method or the multi-model/multiphysics method. In fact, the mean of an ensemble forecast offers a better forecast than a deterministic (or control) forecast after a short lead time (3 5 days) for global modelling applications. There is about a 1-2-day improvement in the forecast skill when using an ensemble mean instead of a single forecast for longer lead-time. The skillful forecast (65% and above of an anomaly correlation) could be extended to 8 days (or longer) by present-day ensemble forecast systems. Furthermore, ensemble forecasts can deliver a probabilistic forecast to the users, which is based on the probability density function (PDF)instead of a single-value forecast from a traditional deterministic system. It has long been recognized that the ensemble forecast not only improves our weather forecast predictability but also offers a remarkable forecast for the future uncertainty, such as the relative measure of predictability (RMOP) and probabilistic quantitative precipitation forecast (PQPF). Not surprisingly, the success of the ensemble forecast and its wide application greatly increase the confidence of model developers and research communities.
Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry.
Chowdhury, Alok Kumar; Tjondronegoro, Dian; Chandran, Vinod; Trost, Stewart G
2017-09-01
To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbor, support vector machine, and neural network). The study used three independent data sets that included wrist-worn accelerometer data. For each data set, a four-step classification framework consisting of data preprocessing, feature extraction, normalization and feature selection, and classifier training and testing was implemented. For the custom ensemble, decisions from the single classifiers were aggregated using three decision fusion methods: weighted majority vote, naïve Bayes combination, and behavior knowledge space combination. Classifiers were cross-validated using leave-one subject out cross-validation and compared on the basis of average F1 scores. In all three data sets, ensemble learning methods consistently outperformed the individual classifiers. Among the conventional ensemble methods, random forest models provided consistently high activity recognition; however, the custom ensemble model using weighted majority voting demonstrated the highest classification accuracy in two of the three data sets. Combining multiple individual classifiers using conventional or custom ensemble learning methods can improve activity recognition accuracy from wrist-worn accelerometer data.
Competitive Learning Neural Network Ensemble Weighted by Predicted Performance
Ye, Qiang
2010-01-01
Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…
Exact ensemble density-functional theory for excited states
Yang, Zeng-hui; Pribram-Jones, Aurora; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A
2014-01-01
We construct exact Kohn-Sham potentials for the ensemble density-functional theory (EDFT) of excited states from the ground and excited states of helium. The exchange-correlation potential is compared with current approximations, which miss prominent features. The ensemble derivative discontinuity is tested, and the virial theorem is proven and illustrated.
An iterative ensemble Kalman filter for reservoir engineering applications
Krymskaya, M.V.; Hanea, R.G.; Verlaan, M.
2009-01-01
The study has been focused on examining the usage and the applicability of ensemble Kalman filtering techniques to the history matching procedures. The ensemble Kalman filter (EnKF) is often applied nowadays to solving such a problem. Meanwhile, traditional EnKF requires assumption of the distributi
Competitive Learning Neural Network Ensemble Weighted by Predicted Performance
Ye, Qiang
2010-01-01
Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…
Modality-Driven Classification and Visualization of Ensemble Variance
Energy Technology Data Exchange (ETDEWEB)
Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.
2016-10-01
Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.
Directory of Open Access Journals (Sweden)
Kazuo Saito
2012-01-01
Full Text Available The effect of lateral boundary perturbations (LBPs on the mesoscale breeding (MBD method and the local ensemble transform Kalman filter (LETKF as the initial perturbations generators for mesoscale ensemble prediction systems (EPSs was examined. A LBPs method using the Japan Meteorological Agency's (JMA's operational one-week global ensemble prediction was developed and applied to the mesoscale EPS of the Meteorological Research Institute for the World Weather Research Programme, Beijing 2008 Olympics Research and Development Project. The amplitude of the LBPs was adjusted based on the ensemble spread statistics considering the difference of the forecast times of the JMA's one-week EPS and the associated breeding/ensemble Kalman filter (EnKF cycles. LBPs in the ensemble forecast increase the ensemble spread and improve the accuracy of the ensemble mean forecast. In the MBD method, if LBPs were introduced in its breeding cycles, the growth rate of the generated bred vectors is increased, and the ensemble spread and the root mean square errors (RMSEs of the ensemble mean are further improved in the ensemble forecast. With LBPs in the breeding cycles, positional correspondences to the meteorological disturbances and the orthogonality of the bred vectors are improved. Brier Skill Scores (BSSs also showed a remarkable effect of LBPs in the breeding cycles. LBPs showed a similar effect with the LETKF. If LBPs were introduced in the EnKF data assimilation cycles, the ensemble spread, ensemble mean accuracy, and BSSs for precipitation were improved, although the relative advantage of LETKF as the initial perturbations generator against MDB was not necessarily clear. LBPs in the EnKF cycles contribute not to the orthogonalisation but to prevent the underestimation of the forecast error near the lateral boundary.The accuracy of the LETKF analyses was compared with that of the mesoscale 4D-VAR analyses. With LBPs in the LETKF cycles, the RMSEs of the
An integrable generalization of the super AKNS hierarchy and its bi-Hamiltonian formulation
Yu, Jing; Ma, Wen-Xiu; Han, Jingwei; Chen, Shouting
2017-02-01
Based on a Lie super-algebra B(0, 1), an integrable generalization of the super AKNS iso-spectral problem is introduced and its corresponding generalized super AKNS hierarchy is generated. By making use of the super-trace identity (or the super variational identity), the resulting super soliton hierarchy can be put into a super bi-Hamiltonian form. A generalized super AKNS soliton hierarchy with self-consistent sources is also presented.
Explosive Super-eruptions: Problems and Prejudices
Self, S.
2010-12-01
A super-eruption is defined as one with a magma yield > 10^15 kg (magnitude (M) 8). The term has mainly been applied to large-scale, caldera and ignimbrite-forming explosive eruptions, but it can be applied to all eruptions that released > 10^15 kg of magma. For effusive volcanism, evidence suggests that individual eruptions of this size ( > ~ 370 km^3 of typical basalt or > 450 km^3 of rhyolite flood lava) arise only during periods of LIP formation. The super-eruption concept raises interesting questions about genesis and storage of magmas that feed these vast events. Deposits of major explosive eruptions are Plinian fallout, ignimbrite sheets, and co-ignimbrite ash fall. Based on earlier suggestions and evidence, widespread outflow ignimbrite (O), co-ignimbrite ash (A), and inter-caldera ignimbrite (I) are all major components of the total super-eruption deposit and may tend towards being subequal. In super-eruption deposits, the reported volume of vent-derived Plinian eruption column fallout is often a minor component of the total volume, yet in several cases (Oruanui, Taupo, 26 ka ago, M 8.1; Bishop Tuff, 760 ka, M 8.2; Bandelier (Otowi) Tuff, 1.6 Ma, M8) it is now recognized that vent-derived columns persisted for most of the eruption. Thus, distally, the ash-fall derived from co-ignimbrite ash clouds may be mixed with contemporaneous fallout from a vertical column. Some major ignimbrites have no reported associated Plinian deposit; the huge Young Toba Tuff (YTT, 74 ka, M 8.8) is a significant example. However, the very widespread Toba ash-fall deposit constitutes ~ 40 % of the total mass of magma erupted and is presumed to be co-ignimbrite. Timing of the onset of column collapse probably controls whether a recognizable Plinian deposit is laid down. All super-eruptions probably produce extensive fallout deposits, and this is generally of vent-derived and pyroclastic-flow-derived origin. Establishing the relationships between large-scale ignimbrites and their
Data assimilation the ensemble Kalman filter
Evensen, Geir
2007-01-01
Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples. Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should b...
Predicting protein dynamics from structural ensembles
Copperman, J
2015-01-01
The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using e...
China’s First Modern Dance Ensemble
Institute of Scientific and Technical Information of China (English)
1992-01-01
After four years’hardwork by both Chineseand foreign artiststhe Guangdong ExperimentalModern Dance Ensemble,thefirst of its kind in China,wasestablished on June 6,1992,in the Friendship Theater ofGuangzhou.Ms、Yang Meiqi,a famous Chinese folk danceeducator,was chosen as headand Mr.Willy Tsao,a famousyoung Hongkong dancer,as artisticdirector.China’s Central TV Stationreported the news.Recommended by Ms.ChiangChing,a Chinese-American dancer,Yang Meiqi went to Durham,NorthCarolina,in the United States in thesummer of 1986.to attend the Amer-ican Dance Festival.The moderndances put on during the festivalfascinated her with their universal“language,”flexible movement,cho-reography and scientific training.“Isn’t this just What China’s dance
ARM Cloud Retrieval Ensemble Data Set (ACRED)
Energy Technology Data Exchange (ETDEWEB)
Zhao, C; Xie, S; Klein, SA; McCoy, R; Comstock, JM; Delanoë, J; Deng, M; Dunn, M; Hogan, RJ; Jensen, MP; Mace, GG; McFarlane, SA; O’Connor, EJ; Protat, A; Shupe, MD; Turner, D; Wang, Z
2011-09-12
This document describes a new Atmospheric Radiation Measurement (ARM) data set, the ARM Cloud Retrieval Ensemble Data Set (ACRED), which is created by assembling nine existing ground-based cloud retrievals of ARM measurements from different cloud retrieval algorithms. The current version of ACRED includes an hourly average of nine ground-based retrievals with vertical resolution of 45 m for 512 layers. The techniques used for the nine cloud retrievals are briefly described in this document. This document also outlines the ACRED data availability, variables, and the nine retrieval products. Technical details about the generation of ACRED, such as the methods used for time average and vertical re-grid, are also provided.
On super edge-graceful trees of diameter four
Krop, E; Raridan, C
2011-01-01
In "On the super edge graceful trees of even orders," Chung, Lee, Gao, and Schaffer posed the following problem: Characterize trees of diameter 4 which are super edge-graceful. In this paper, we provide super edge-graceful labelings for all caterpillars and even size lobsters of diameter 4 which permit such labelings. We also provide super edge-graceful labelings for several families of odd size lobsters of diameter 4.
An educational model for ensemble streamflow simulation and uncertainty analysis
Directory of Open Access Journals (Sweden)
A. AghaKouchak
2013-02-01
Full Text Available This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.
Ensemble inequivalence: Landau theory and the ABC model
Cohen, O.; Mukamel, D.
2012-12-01
It is well known that systems with long-range interactions may exhibit different phase diagrams when studied within two different ensembles. In many of the previously studied examples of ensemble inequivalence, the phase diagrams differ only when the transition in one of the ensembles is first order. By contrast, in a recent study of a generalized ABC model, the canonical and grand-canonical ensembles of the model were shown to differ even when they both exhibit a continuous transition. Here we show that the order of the transition where ensemble inequivalence may occur is related to the symmetry properties of the order parameter associated with the transition. This is done by analyzing the Landau expansion of a generic model with long-range interactions. The conclusions drawn from the generic analysis are demonstrated for the ABC model by explicit calculation of its Landau expansion.
Excitations and benchmark ensemble density functional theory for two electrons
Pribram-Jones, Aurora; Trail, John R; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A
2014-01-01
A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange (SEHX), is derived. Exact conditions that are proven include the signs of the correlation energy components, the virial theorem for both exchange and correlation, and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.
Excitations and benchmark ensemble density functional theory for two electrons
Energy Technology Data Exchange (ETDEWEB)
Pribram-Jones, Aurora; Burke, Kieron [Department of Chemistry, University of California-Irvine, Irvine, California 92697 (United States); Yang, Zeng-hui; Ullrich, Carsten A. [Department of Physics and Astronomy, University of Missouri, Columbia, Missouri 65211 (United States); Trail, John R.; Needs, Richard J. [Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE (United Kingdom)
2014-05-14
A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two-electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange, is derived. Exact conditions that are proven include the signs of the correlation energy components and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.
Adaptive calibration of (u,v)‐wind ensemble forecasts
DEFF Research Database (Denmark)
Pinson, Pierre
2012-01-01
Ensemble forecasts of (u,v)‐wind are of crucial importance for a number of decision‐making problems related to e.g. air traffic control, ship routeing and energy management. The skill of these ensemble forecasts as generated by NWP‐based models can be maximised by correcting for their lack...... of sufficient reliability. The original framework introduced here allows for an adaptive bivariate calibration of these ensemble forecasts. The originality of this methodology lies in the fact that calibrated ensembles still consist of a set of (space–time) trajectories, after translation and dilation...... on the adaptive calibration of ECMWF ensemble forecasts of (u,v)‐wind at 10 m above ground level over Europe over a three‐year period between December 2006 and December 2009. Substantial improvements in (bivariate) reliability and in various deterministic/probabilistic scores are observed. Finally, the maps...
Induced Ginibre ensemble of random matrices and quantum operations
Fischmann, J; Khoruzhenko, B A; Sommers, H -J; Zyczkowski, K
2011-01-01
A generalisation of the Ginibre ensemble of non-Hermitian random square matrices is introduced. The corresponding probability measure is induced by the ensemble of rectangular Gaussian matrices via a quadratisation procedure. We derive the joint probability density of eigenvalues for such induced Ginibre ensemble and study various spectral correlation functions for complex and real matrices, and analyse universal behaviour in the limit of large dimensions. In this limit the eigenvalues of the induced Ginibre ensemble cover uniformly a ring in the complex plane. The real induced Ginibre ensemble is shown to be useful to describe statistical properties of evolution operators associated with random quantum operations, for which the dimensions of the input state and the output state do differ.
Discrete post-processing of total cloud cover ensemble forecasts
Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian
2017-04-01
This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.
Halu, Arda; Bianconi, Ginestra
2013-01-01
Spatial networks range from the brain networks, to transportation networks and infrastructures. Recently interacting and multiplex networks are attracting great attention because their dynamics and robustness cannot be understood without treating at the same time several networks. Here we present maximal entropy ensembles of spatial multiplex and spatial interacting networks that can be used in order to model spatial multilayer network structures and to build null models of real datasets. We show that spatial multiplex naturally develop a significant overlap of the links, a noticeable property of many multiplexes that can affect significantly the dynamics taking place on them. Additionally, we characterize ensembles of spatial interacting networks and we analyse the structure of interacting airport and railway networks in India, showing the effect of space in determining the link probability.
Ensemble Bayesian forecasting system Part I: Theory and algorithms
Herr, Henry D.; Krzysztofowicz, Roman
2015-05-01
The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of
The structure of the super-W∞(λ) algebra
Bergshoeff, E.; Wit, B. de; Vasiliev, M.
1991-01-01
We give a comprehensive treatment of the super-W∞(λ) algebra, an extension of the super-Virasoro algebra that contains generators of spin s ≥ ½. The parameter λ defines the embedding of the Virasoro subalgebra. We describe how to obtain the super-W∞(λ) algebra from the associative algebra of
Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter
Luo, Xiaodong
2011-12-01
A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used in the Kalman filter. By design, the H∞ filter is more robust than the Kalman filter, in the sense that the estimation error in the H∞ filter in general has a finite growth rate with respect to the uncertainties in assimilation, except for a special case that corresponds to the Kalman filter. The original form of the H∞ filter contains global constraints in time, which may be inconvenient for sequential data assimilation problems. Therefore a variant is introduced that solves some time-local constraints instead, and hence it is called the time-local H∞ filter (TLHF). By analogy to the ensemble Kalman filter (EnKF), the concept of ensemble time-local H∞ filter (EnTLHF) is also proposed. The general form of the EnTLHF is outlined, and some of its special cases are discussed. In particular, it is shown that an EnKF with certain covariance inflation is essentially an EnTLHF. In this sense, the EnTLHF provides a general framework for conducting covariance inflation in the EnKF-based methods. Some numerical examples are used to assess the relative robustness of the TLHF–EnTLHF in comparison with the corresponding KF–EnKF method.
Super ready: how a regional approach to Super Bowl EMS paid off.
Clancy, Terry; Cortacans, Henry P
2014-07-01
The Super Bowl and its associated activities represent one of the largest special events in the world. Super Bowl XLVIII was geographically unique because the NFL's and Super Bowl Host Committee's activities, venues and events encompassed two states and fell across numerous jurisdictions within six counties (Bergen, Hudson, Morris, Essex, Middlesex, and Manhattan).This Super Bowl was the first to do this. EMS was one of the largest operational components during this event. Last and most important, it is the people and relationships that make any planning initiative and event a success. Sit down and have a cup a coffee with your colleagues, partners and neighbors in and out of state to discuss your planning initiatives. Do it early-it will make your efforts less painful should an event of this magnitude come to a city near you!
Acoustic Design of Super-light Structures
DEFF Research Database (Denmark)
Christensen, Jacob Ellehauge; Hertz, Kristian Dahl; Brunskog, Jonas
aggregate (leca) along with a newly developed technology called pearl-chain reinforcement, which is a system for post-tensioning. Here, it is shown how to combine these technologies within a precast super-light slab element, while honoring the requirements of a holistic design. Acoustic experiments...
Folded shapes with Super-Light Structures
DEFF Research Database (Denmark)
Castberg, Niels Andreas; Hertz, Kristian Dahl
2012-01-01
The use of folded shapes in structures has become more common, but it still costs problems because of construction issues and bending moments. The present paper deals with how the newly patented structural concept Super-Light structures (SLS) can be used to create folded shapes. SLS gives lighter...
Single Image Super Resolution via Sparse Reconstruction
Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.
2012-01-01
High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms. Limita
Conformal anomaly of super Wilson loop
Energy Technology Data Exchange (ETDEWEB)
Belitsky, A.V., E-mail: andrei.belitsky@asu.edu [Department of Physics, Arizona State University, Tempe, AZ 85287-1504 (United States)
2012-09-11
Classically supersymmetric Wilson loop on a null polygonal contour possesses all symmetries required to match it onto non-MHV amplitudes in maximally supersymmetric Yang-Mills theory. However, to define it quantum mechanically, one is forced to regularize it since perturbative loop diagrams are not well defined due to presence of ultraviolet divergences stemming from integration in the vicinity of the cusps. A regularization that is adopted by practitioners by allowing one to use spinor helicity formalism, on the one hand, and systematically go to higher orders of perturbation theory is based on a version of dimensional regularization, known as Four-Dimensional Helicity scheme. Recently it was demonstrated that its use for the super Wilson loop at one loop breaks both conformal symmetry and Poincare supersymmetry. Presently, we exhibit the origin for these effects and demonstrate how one can undo this breaking. The phenomenon is alike the one emerging in renormalization group mixing of conformal operators in conformal theories when one uses dimensional regularization. The rotation matrix to the diagonal basis is found by means of computing the anomaly in the Ward identity for the conformal boost. Presently, we apply this ideology to the super Wilson loop. We compute the one-loop conformal anomaly for the super Wilson loop and find that the anomaly depends on its Grassmann coordinates. By subtracting this anomalous contribution from the super Wilson loop we restore its interpretation as a dual description for reduced non-MHV amplitudes which are expressed in terms of superconformal invariants.
Super-Kamiokande worth full restoration
Mishima, I
2002-01-01
While prospects are good that the SuperKamiokande facility will be partially repaired after an accident last November, the government has yet to confirm whether it will spend the estimated 2.5 billion yen needed for a full-scale restoration (1 page).
Structural optimization of super-repellent surfaces
DEFF Research Database (Denmark)
Cavalli, Andrea; Bøggild, Peter; Okkels, Fridolin
2013-01-01
Micro-patterning is an effective way to achieve surfaces with extreme liquid repellency. This technique does not rely on chemical coatings and is therefore a promising concept for application in food processing and bio-compatibile coatings. This super-repellent behaviour is obtained by suspending...
Facile preparation of super durable superhydrophobic materials.
Wu, Lei; Zhang, Junping; Li, Bucheng; Fan, Ling; Li, Lingxiao; Wang, Aiqin
2014-10-15
The low stability, complicated and expensive fabrication procedures seriously hinder practical applications of superhydrophobic materials. Here we report an extremely simple method for preparing super durable superhydrophobic materials, e.g., textiles and sponges, by dip coating in fluoropolymers (FPs). The morphology, surface chemical composition, mechanical, chemical and environmental stabilities of the superhydrophobic textiles were investigated. The results show how simple the preparation of super durable superhydrophobic textiles can be! The superhydrophobic textiles outperform their natural counterparts and most of the state-of-the-art synthetic superhydrophobic materials in stability. The intensive mechanical abrasion, long time immersion in various liquids and repeated washing have no obvious influence on the superhydrophobicity. Water drops are spherical in shape on the samples and could easily roll off after these harsh stability tests. In addition, this simple dip coating approach is applicable to various synthetic and natural textiles and can be easily scaled up. Furthermore, the results prove that a two-tier roughness is helpful but not essential with regard to the creation of super durable superhydrophobic textiles. The combination of microscale roughness of textiles and materials with very low surface tension is enough to form super durable superhydrophobic textiles. According to the same procedure, superhydrophobic polyurethane sponges can be prepared, which show high oil absorbency, oil/water separation efficiency and stability. Copyright © 2014 Elsevier Inc. All rights reserved.
Pavement behaviour under the super single tyre
CSIR Research Space (South Africa)
Viljoen, AW
1982-06-01
Full Text Available Pavement behaviour under the super single tyre (SST) was investigated and compared with that under a conventional dual tyre (CDT). Contact areas and contact pressures over a range of loading conditions were measured and compared. Two approaches were...
Typhoon effects on super-tall buildings
Li, Q. S.; Xiao, Y. Q.; Wu, J. R.; Fu, J. Y.; Li, Z. N.
2008-06-01
Full-scale measurement is considered to be the most reliable method for evaluating wind effects on buildings and structures. This paper presents selected results of wind characteristics and structural responses measured from four super-tall buildings, The Center (350 m high, 79 floors) in Hong Kong, Di Wang Tower (384 m high, 78 floors) in Shenzhen, CITIC Plaza Tower (391 m high, 80 floors) in Guangzhou and Jin Mao Building (421 m high, 88 floors) in Shanghai, during the passages of three typhoons. The field data such as wind speed, wind direction and acceleration responses, etc., were continuously measured from the super-tall buildings during the typhoons. Detailed analysis of the field data was conducted to investigate the characteristics of typhoon-generated wind and wind-induced vibrations of these super-tall buildings under typhoon conditions. The dynamic characteristics of the tall buildings were determined from the field measurements and comparisons with those calculated from the finite element (FE) models of the structures were made. Furthermore, the full-scale measurements were compared with wind tunnel results to evaluate the accuracy of the model test results and the adequacy of the techniques used in the wind tunnel tests. The results presented in this paper are expected to be of considerable interest and of use to researchers and professionals involved in designing super-tall buildings.
Searching for Frozen Super Earth via Microlensing
Batista, V.; Beaulieu, J. P.; Cassan, A.; Coutures, C.; Donatowicz, J.; Fouqué, P.; Kubas, D.; Marquette, J. B.
2009-04-01
Microlensing planet hunt is a unique method to probe efficiently for frozen Super Earth orbiting the most common stars of our galaxy. It is nicely complementing the parameter space probed by very high accuracy radial velocity measurements and future space based detections of low mass transiting planets. In order to maximize the planet catch, the microlensing community is engaged in a total cooperation among the different groups (OGLE, MicroFUN, MOA, PLANET/RoboNET) by making the real time data available, and mutual informing/reporting about modeling efforts. Eight planets have been published so far by combinations of the different groups, 4 Jovian analogues, one Neptune and two Super Earth. Given the microlensing detection efficiency, it suggests that these Neptunes/Super Earths may be quite common. Using networks of dedicated 1-2m class telescopes, the microlensing community has entered a new phase of planet discoveries, and will be able to provide constraints on the abundance of frozen Super-Earths in the near future. Statistics about Mars to Earth mass planets, extending to the habitable zone will be achieved with space based wide field imagers (EUCLID) at the horizon 2017.
Folded shapes with Super-Light Structures
DEFF Research Database (Denmark)
Castberg, Niels Andreas; Hertz, Kristian Dahl
2012-01-01
The use of folded shapes in structures has become more common, but it still costs problems because of construction issues and bending moments. The present paper deals with how the newly patented structural concept Super-Light structures (SLS) can be used to create folded shapes. SLS gives lighter...
Advantages of super-light structures
DEFF Research Database (Denmark)
Hertz, Kristian Dahl
2009-01-01
Super-light structures with pearl-chain reinforcement is a new revolutionary technology that opens possibilities of building load-bearing structures much cheaper and with several other advantages compared to traditional constructions of concrete and steel. Some benefits are: 1 Half price or less. 2...
Super-resolution near field imaging device
DEFF Research Database (Denmark)
2014-01-01
Super-resolution imaging device comprising at least a first and a second elongated coupling element, each having a first transverse dimension at a first end and a second transverse dimension at a second end and being adapted for guiding light between their respective first and second ends, each...
Viney, N.R.; Bormann, H.; Breuer, L.; Bronstert, A.; Croke, B.F.W.; Frede, H.; Graff, T.; Hubrechts, L.; Huisman, J.A.; Jakeman, A.J.; Kite, G.W.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Willems, P.
2009-01-01
This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in
BREEDING SUPER-EARTHS AND BIRTHING SUPER-PUFFS IN TRANSITIONAL DISKS
Energy Technology Data Exchange (ETDEWEB)
Lee, Eve J.; Chiang, Eugene, E-mail: evelee@berkeley.edu, E-mail: echiang@astro.berkeley.edu [Department of Astronomy, University of California Berkeley, Berkeley, CA 94720-3411 (United States)
2016-02-01
The riddle posed by super-Earths (1–4R{sub ⊕}, 2–20M{sub ⊕}) is that they are not Jupiters: their core masses are large enough to trigger runaway gas accretion, yet somehow super-Earths accreted atmospheres that weigh only a few percent of their total mass. We show that this puzzle is solved if super-Earths formed late, as the last vestiges of their parent gas disks were about to clear. This scenario would seem to present fine-tuning problems, but we show that there are none. Ambient gas densities can span many (in one case up to 9) orders of magnitude, and super-Earths can still robustly emerge after ∼0.1–1 Myr with percent-by-weight atmospheres. Super-Earth cores are naturally bred in gas-poor environments where gas dynamical friction has weakened sufficiently to allow constituent protocores to gravitationally stir one another and merge. So little gas is present at the time of core assembly that cores hardly migrate by disk torques: formation of super-Earths can be in situ. The basic picture—that close-in super-Earths form in a gas-poor (but not gas-empty) inner disk, fed continuously by gas that bleeds inward from a more massive outer disk—recalls the largely evacuated but still accreting inner cavities of transitional protoplanetary disks. We also address the inverse problem presented by super-puffs: an uncommon class of short-period planets seemingly too voluminous for their small masses (4–10R{sub ⊕}, 2–6M{sub ⊕}). Super-puffs most easily acquire their thick atmospheres as dust-free, rapidly cooling worlds outside ∼1 AU where nebular gas is colder, less dense, and therefore less opaque. Unlike super-Earths, which can form in situ, super-puffs probably migrated in to their current orbits; they are expected to form the outer links of mean-motion resonant chains, and to exhibit greater water content. We close by confronting observations and itemizing remaining questions.
SuperB A High-Luminosity Asymmetric $e^+ e^-$ Super Flavour Factory : Conceptual Design Report
Bona, M.; Grauges Pous, E.; Colangelo, P.; De Fazio, F.; Palano, A.; Manghisoni, M.; Re, V.; Traversi, G.; Eigen, G.; Venturini, M.; Soni, N.; Bruschi, M.; De Castro, S.; Faccioli, P.; Gabrieli, A.; Giacobbe, B.; Semprini Cesare, N.; Spighi, R.; Villa, M.; Zoccoli, A.; Hearty, C.; McKenna, J.; Soni, A.; Khan, A.; Barniakov, A.Y.; Barniakov, M.Y.; Blinov, V.E.; Druzhinin, V.P.; Golubev, V.B.; Kononov, S.A.; Koop, I.A.; Kravchenko, E.A.; Levichev, E.B.; Nikitin, S.A.; Onuchin, A.P.; Piminov, P.A.; Serednyakov, S.I.; Shatilov, D.N.; Skovpen, Y.I.; Solodov, E.A.; Cheng, C.H.; Echenard, B.; Fang, F.; Hitlin, D.J.; Porter, F.C.; Asner, D.M.; Pham, T.N.; Fleischer, R.; Giudice, G.F.; Hurth, T.; Mangano, M.; Mancinelli, G.; Meadows, B.T.; Schwartz, A.J.; Sokoloff, M.D.; Soffer, A.; Beard, C.D.; Haas, T.; Mankel, R.; Hiller, G.; Ball, P.; Pappagallo, M.; Pennington, M.R.; Gradl, W.; Playfer, S.; Abada, A.; Becirevic, D.; Descotes-Genon, S.; Pene, O.; Andreotti, D.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabresi, R.; Cecchi, A.; Cibinetto, G.; Franchini, P.; Luppi, E.; Negrini, M.; Petrella, A.; Piemontese, L.; Prencipe, E.; Santoro, V.; Stancari, G.; Anulli, F.; Baldini-Ferroli, R.; Biagini, M.E.; Boscolo, M.; Calcaterra, A.; Drago, A.; Finocchiaro, G.; Guiducci, S.; Isidori, G.; Pacetti, S.; Patteri, P.; Peruzzi, I.M.; Piccolo, M.; Preger, M.A.; Raimondi, P.; Rama, M.; Vaccarezza, C.; Zallo, A.; Zobov, M.; De Sangro, R.; Buzzo, A.; Lo Vetere, M.; Macri, M.; Monge, M.R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Tosi, S.; Matias, J.; Panduro Vazquez, W.; Borzumati, F.; Eyges, V.; Prell, S.A.; Pedlar, T.K.; Korpar, S.; Pestonik, R.; Staric, M.; Neubert, M.; Denig, A.G.; Nierste, U.; Agoh, T.; Ohmi, K.; Ohnishi, Y.; Fry, J.R.; Touramanis, C.; Wolski, A.; Golob, B.; Krizan, P.; Flaecher, H.; Bevan, A.J.; Di Lodovico, F.; George, K.A.; Barlow, R.; Lafferty, G.; Jawahery, A.; Roberts, D.A.; Simi, G.; Patel, P.M.; Robertson, S.H.; Lazzaro, A.; Palombo, F.; Kaidalov, A.; Buras, A.J.; Tarantino, C.; Buchalla, G.; Sanda, A.I.; D'Ambrosio, G.; Ricciardi, G.; Bigi, I.; Jessop, C.P.; Losecco, J.M.; Honscheid, K.; Arnaud, N.; Chehab, R.; Fedala, Y.; Polci, F.; Roudeau, P.; Sordini, V.; Soskov, V.; Stocchi, A.; Variola, A.; Vivoli, A.; Wormser, G.; Zomer, F.; Bertolin, A.; Brugnera, R.; Gagliardi, N.; Gaz, A.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Bonneaud, G.R.; Lombardo, V.; Calderini, G.; Ratti, L.; Speziali, V.; Biasini, M.; Covarelli, R.; Manoni, E.; Servoli, L.; Angelini, C.; Batignani, G.; Bettarini, S.; Bosi, F.; Carpinelli, M.; Cenci, R.; Cervelli, A.; Dell'Orso, M.; Forti, F.; Giannetti, P.; Giorgi, M.; Lusiani, A.; Marchiori, G.; Massa, M.; Mazur, M.A.; Morsani, F.; Neri, N.; Paoloni, E.; Raffaelli, F.; Rizzo, G.; Walsh, J.; Braun, V.; Lenz, A.; Adams, G.S.; Danko, I.Z.; Baracchini, E.; Bellini, F.; Cavoto, G.; D'Orazio, A.; Del Re, D.; Di Marco, E.; Faccini, R.; Ferrarotto, F.; Gaspero, Mario; Jackson, P.; Martinelli, G.; Mazzoni, M.A.; Morganti, Silvio; Piredda, G.; Renga, F.; Silvestrini, L.; Voena, C.; Catani, L.; Di Ciaccio, A.; Messi, R.; Santovetti, E.; Satta, A.; Ciuchini, M.; Lubicz, V.; Wilson, F.F.; Godang, R.; Chen, X.; Liu, H.; Park, W.; Purohit, M.; Trivedi, A.; White, R.M.; Wilson, J.R.; Allen, M.T.; Aston, D.; Bartoldus, R.; Brodsky, S.J.; Cai, Y.; Coleman, J.; Convery, M.R.; DeBarger, S.; Dingfelder, J.C.; Dubois-Felsmann, G.P.; Ecklund, S.; Fisher, A.S.; Haller, G.; Heifets, S.A.; Kaminski, J.; Kelsey, M.H.; Kocian, M.L.; Leith, D.W.G.S.; Li, N.; Luitz, S.; Luth, V.; MacFarlane, D.; Messner, R.; Muller, D.R.; Nosochkov, Y.; Novokhatski, A.; Pivi, M.; Ratcliff, B.N.; Roodman, A.; Schwiening, J.; Seeman, J.; Snyder, A.; Sullivan, M.; Va'Vra, J.; Wienands, U.; Wisniewski, W.; Stoeck, H.; Cheng, H.Y.; Li, H.N.; Keum, Y.Y.; Gronau, M.; Grossman, Y.; Bianchi, F.; Gamba, D.; Gambino, P.; Marchetto, F.; Menichetti, Ezio A.; Mussa, R.; Pelliccioni, M.; Dalla Betta, G.F.; Bomben, M.; Bosisio, L.; Cartaro, C.; Lanceri, L.; Vitale, L.; Azzolini, V.; Bernabeu, J.; Lopez-March, N.; Martinez-Vidal, F.; Milanes, D.A.; Oyanguren, A.; Paradisi, P.; Pich, A.; Sanchis-Lozano, M.A.; Kowalewski, Robert V.; Roney, J.M.; Back, J.J.; Gershon, T.J.; Harrison, P.F.; Latham, T.E.; Mohanty, G.B.; Petrov, A.A.; Pierini, M.; INFN
2007-01-01
The physics objectives of SuperB, an asymmetric electron-positron collider with a luminosity above 10^36/cm^2/s are described, together with the conceptual design of a novel low emittance design that achieves this performance with wallplug power comparable to that of the current B Factories, and an upgraded detector capable of doing the physics in the SuperB environment.
Institute of Scientific and Technical Information of China (English)
Yan Xia REN
2008-01-01
The global supports of super-Poisson processes and super-random walks with a branching mechanism ψ(z)=z2 and constant branching rate are known to be noncompact. It turns out that, for any spatially dependent branching rate, this property remains true. However, the asymptotic extinction property for these two kinds of superprocesses depends on the decay rate of the branching-rate function at infinity.
Super-resolution imaging in optical scanning holography using structured illumination
Ren, Zhenbo; Lam, Edmund Y.
2016-10-01
As a specific digital holographic microscopy system, optical scanning holography (OSH) is an appealing technique that makes use of the advantages of holography in the application of optical microscopy. In OSH system, a three-dimensional object is scanned with a Fresnel zone plate in a raster fashion, and the electrical signals are demodulated into a complex hologram by heterodyne detection. Then the recorded light wavefront information contained in the hologram allows one to digitally reconstruct the specimen for multiple purposes such as optical sectioning, extended focused imaging as well as three-dimensional imaging. According to Abbe criterion, however, akin to those conventional microscopic imaging systems, OSH suffers from limited resolving power due to the finite sizes of the objective lens and the aperture, i.e., low numerical aperture. To bypass the diffraction barrier in light microscopy, various super-resolution imaging techniques have been proposed. Among those methods, structured illumination is an ensemble imaging concept that modulates the spatial frequency by projecting additional well-defined patterns with different orientation and phase shift onto the specimen. Computational algorithms are then applied to remove the effect of the structure and to reconstruct a super-resolved image beyond the diffraction-limit. In this paper, we introduce this technique in OSH system to scale down the spatial resolution beyond the diffraction limit. The performance of the proposed method is validated by simulation and experimental results.
Verma, Navneet C.; Khan, Syamantak; Nandi, Chayan K.
2016-12-01
The advancement of high-resolution bioimaging has always been dependent on the discovery of bright and easily available fluorescent probes. Fluorescent carbon nanodots, an interesting class of relatively new nanomaterials, have emerged as a versatile alternative due to their superior optical properties, non-toxicity, cell penetrability and easy routes to synthesis. Although a plethora of reports is available on bioimaging using carbon dots, single-molecule-based super-resolution imaging is rare in the literature. In this study, we have systematically characterized the single-molecule fluorescence of three carbon dots and compared them with a standard fluorescent probe. Each of these carbon dots showed a long-lived dark state in the presence of an electron acceptor. The electron transfer mechanism was investigated in single-molecule as well as in ensemble experiments. The average on-off rate between the fluorescent bright and dark states, which is one of the important parameters for single-molecule localization-based super-resolution microscopy, was measured by changing the laser power. We report that the photon budget and on-off rate of these carbon dots were good enough to achieve single-molecule localization with a precision of ~35 nm.
Ensemble Kalman filtering without the intrinsic need for inflation
Directory of Open Access Journals (Sweden)
M. Bocquet
2011-10-01
Full Text Available The main intrinsic source of error in the ensemble Kalman filter (EnKF is sampling error. External sources of error, such as model error or deviations from Gaussianity, depend on the dynamical properties of the model. Sampling errors can lead to instability of the filter which, as a consequence, often requires inflation and localization. The goal of this article is to derive an ensemble Kalman filter which is less sensitive to sampling errors. A prior probability density function conditional on the forecast ensemble is derived using Bayesian principles. Even though this prior is built upon the assumption that the ensemble is Gaussian-distributed, it is different from the Gaussian probability density function defined by the empirical mean and the empirical error covariance matrix of the ensemble, which is implicitly used in traditional EnKFs. This new prior generates a new class of ensemble Kalman filters, called finite-size ensemble Kalman filter (EnKF-N. One deterministic variant, the finite-size ensemble transform Kalman filter (ETKF-N, is derived. It is tested on the Lorenz '63 and Lorenz '95 models. In this context, ETKF-N is shown to be stable without inflation for ensemble size greater than the model unstable subspace dimension, at the same numerical cost as the ensemble transform Kalman filter (ETKF. One variant of ETKF-N seems to systematically outperform the ETKF with optimally tuned inflation. However it is shown that ETKF-N does not account for all sampling errors, and necessitates localization like any EnKF, whenever the ensemble size is too small. In order to explore the need for inflation in this small ensemble size regime, a local version of the new class of filters is defined (LETKF-N and tested on the Lorenz '95 toy model. Whatever the size of the ensemble, the filter is stable. Its performance without inflation is slightly inferior to that of LETKF with optimally tuned inflation for small interval between updates, and
Decadal climate predictions improved by ocean ensemble dispersion filtering
Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.
2017-06-01
Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.type="synopsis">type="main">Plain Language SummaryDecadal predictions aim to predict the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. The ocean memory due to its heat capacity holds big potential skill. In recent years, more precise initialization techniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions. Ensembles are another important aspect. Applying slightly perturbed predictions to trigger the famous butterfly effect results in an ensemble. Instead of evaluating one prediction, but the
Han, Jingwei; Yu, Jing
2017-03-01
Starting from a 3 × 3 matrix-valued spectral problem associated with a Lie superalgebra sl(2|1), a generalized super Ablowitz-Kaup-Newell-Segur (AKNS) hierarchy is derived. The resulting super AKNS hierarchy has a super bi-Hamiltonian structure by the supertrace identity.
Super SI燃烧方式试验研究%Super SI Combustion Mode
Institute of Scientific and Technical Information of China (English)
沈义涛; 吕世亮; 尹琪; 杨嘉林; 高卫民
2011-01-01
The super spark ignition (Super SI) combustion mode, which was the ignition combustion of lean mixture at the temperature of close spontaneous combustion, was researched and its combustion characteristic and feasibility were analyzed.The results indicate that the increase of intake temperature can reduce the cyclic variation of Pmi obviously, shorten the combustion duration and extend the lean limit of SI combustion under the condition of lean mixture. Accordingly, Super SI combustion has the advantages of high thermal efficiency and controllable combustion process.%研究了Super Spark Ignition(Super SI)燃烧方式,即稀薄混合气在近自燃温度状态下点燃燃烧,分析了这种燃烧方式的可行性和燃烧特性.研究结果表明,混合气稀薄时提高发动机的进气温度可显著降低平均指示压力(pmi)的循环波动,缩短燃烧持续期,拓展点燃燃烧的稀薄极限;Super SI燃烧方式具有热效率高、燃烧过程可控的优点.
The 2015 super-resolution microscopy roadmap
Hell, Stefan W.; Sahl, Steffen J.; Bates, Mark; Zhuang, Xiaowei; Heintzmann, Rainer; Booth, Martin J.; Bewersdorf, Joerg; Shtengel, Gleb; Hess, Harald; Tinnefeld, Philip; Honigmann, Alf; Jakobs, Stefan; Testa, Ilaria; Cognet, Laurent; Lounis, Brahim; Ewers, Helge; Davis, Simon J.; Eggeling, Christian; Klenerman, David; Willig, Katrin I.; Vicidomini, Giuseppe; Castello, Marco; Diaspro, Alberto; Cordes, Thorben
2015-11-01
Far-field optical microscopy using focused light is an important tool in a number of scientific disciplines including chemical, (bio)physical and biomedical research, particularly with respect to the study of living cells and organisms. Unfortunately, the applicability of the optical microscope is limited, since the diffraction of light imposes limitations on the spatial resolution of the image. Consequently the details of, for example, cellular protein distributions, can be visualized only to a certain extent. Fortunately, recent years have witnessed the development of ‘super-resolution’ far-field optical microscopy (nanoscopy) techniques such as stimulated emission depletion (STED), ground state depletion (GSD), reversible saturated optical (fluorescence) transitions (RESOLFT), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) or saturated structured illumination microscopy (SSIM), all in one way or another addressing the problem of the limited spatial resolution of far-field optical microscopy. While SIM achieves a two-fold improvement in spatial resolution compared to conventional optical microscopy, STED, RESOLFT, PALM/STORM, or SSIM have all gone beyond, pushing the limits of optical image resolution to the nanometer scale. Consequently, all super-resolution techniques open new avenues of biomedical research. Because the field is so young, the potential capabilities of different super-resolution microscopy approaches have yet to be fully explored, and uncertainties remain when considering the best choice of methodology. Thus, even for experts, the road to the future is sometimes shrouded in mist. The super-resolution optical microscopy roadmap of Journal of Physics D: Applied Physics addresses this need for clarity. It provides guidance to the outstanding questions through a collection of short review articles from experts in the field, giving a thorough
The Solution Construction of Heterotic Super-Liouville Model
Institute of Scientific and Technical Information of China (English)
YANG Zhan-Ying; ZHEN Yi
2001-01-01
We investigate the heterotic super-Liouville model on the base of the basic Lie super-algebra Osp(1|2).Using the super extension of Leznov-Saveliev analysis and Drinfeld Sokolov linear system, we construct the explicit solution of the heterotic super-Liouville system in component form. We also show that the solutions are local and periodic by calculating the exchange relation of the solution. Finally starting from the action of heterotic super-Liou ville model, we obtain the conserved current and conserved charge which possessed the BR ST properties.
A modified iterative ensemble Kalman filter data assimilation method
Xu, Baoxiong; Bai, Yulong; Wang, Yizhao; Li, Zhe; Ma, Boyang
2017-08-01
High nonlinearity is a typical characteristic associated with data assimilation systems. Additionally, iterative ensemble based methods have attracted a large amount of research attention, which has been focused on dealing with nonlinearity problems. To solve the local convergence problem of the iterative ensemble Kalman filter, a modified iterative ensemble Kalman filter algorithm was put forward, which was based on a global convergence strategy from the perspective of a Gauss-Newton iteration. Through self-adaption, the step factor was adjusted to enable every iteration to approach expected values during the process of the data assimilation. A sensitivity experiment was carried out in a low dimensional Lorenz-63 chaotic system, as well as a Lorenz-96 model. The new method was tested via ensemble size, observation variance, and inflation factor changes, along with other aspects. Meanwhile, comparative research was conducted with both a traditional ensemble Kalman filter and an iterative ensemble Kalman filter. The results showed that the modified iterative ensemble Kalman filter algorithm was a data assimilation method that was able to effectively estimate a strongly nonlinear system state.
2009-01-01
Universita Politecnica delle Marche. Ancona. Italy 1 Meteorological and hydrological service. Zagreb. Croatia " MARE-CHER. University of Liege ...continental shelf. Mem. Soc. R. Sci. Liege 6 (10), 141-164. Galmarini. S.. Bianconi, R., Addis. R.. Andronopoulos. S., Astrup. P., Bartzis. J.C
2009-10-08
Finally, lets note that the HE methods, inclusive the "tricks" (discussed in Section 3), might actually also account for the slip and leeway...predicted by each individual model are represented by a colored segment. The actual forecast starts at the brown diamond, the pink diamond represents...unstratihed conditions. Journal of Geophysical Research, 111. Rixen. M., Book, J., Carta , A.. Grandi, V., Gualdesi, L. Stoner, R.. Ranelli. P.. Cavanna
Soil texture reclassification by an ensemble model
Cisty, Milan; Hlavcova, Kamila
2015-04-01
a prerequisite for solving some subsequent task, this bias is propagated to the subsequent modelling or other work. Therefore, for the sake of achieving more general and precise outputs while solving such tasks, the authors of the present paper are proposing a hybrid approach, which has the potential for obtaining improved results. Although the authors continue recommending the use of the mentioned parametric PSD models in the proposed methodology, the final prediction is made by an ensemble machine learning algorithm based on regression trees, the so-called Random Forest algorithm, which is built on top of the outputs of such models, which serves as an ensemble members. An improvement in precision was proved, and it is documented in the paper that the ensemble model worked better than any of its constituents. References Nemes, A., Wosten, J.H.M., Lilly, A., Voshaar, J.H.O.: Evaluation of different procedures to interpolate particle-size distributions to achieve compatibility within soil databases. Geoderma 90, 187- 202 (1999) Hwang, S.: Effect of texture on the performance of soil particle-size distribution models. Geoderma 123, 363-371 (2004) Botula, Y.D., Cornelis, W.M., Baert, G., Mafuka, P., Van Ranst, E.: Particle size distribution models for soils of the humid tropics. J Soils Sediments. 13, 686-698 (2013)
Ensemble Deep Learning for Biomedical Time Series Classification
Directory of Open Access Journals (Sweden)
Lin-peng Jin
2016-01-01
Full Text Available Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.
Ensemble Deep Learning for Biomedical Time Series Classification.
Jin, Lin-Peng; Dong, Jun
2016-01-01
Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.
Ensemble Deep Learning for Biomedical Time Series Classification
2016-01-01
Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.
An Improved Particle Swarm Optimization Algorithm Based on Ensemble Technique
Institute of Scientific and Technical Information of China (English)
SHI Yan; HUANG Cong-ming
2006-01-01
An improved particle swarm optimization (PSO) algorithm based on ensemble technique is presented. The algorithm combines some previous best positions (pbest) of the particles to get an ensemble position (Epbest), which is used to replace the global best position (gbest). It is compared with the standard PSO algorithm invented by Kennedy and Eberhart and some improved PSO algorithms based on three different benchmark functions. The simulation results show that the improved PSO based on ensemble technique can get better solutions than the standard PSO and some other improved algorithms under all test cases.
Deterministic entanglement of Rydberg ensembles by engineered dissipation
DEFF Research Database (Denmark)
Dasari, Durga; Mølmer, Klaus
2014-01-01
We propose a scheme that employs dissipation to deterministically generate entanglement in an ensemble of strongly interacting Rydberg atoms. With a combination of microwave driving between different Rydberg levels and a resonant laser coupling to a short lived atomic state, the ensemble can...... be driven towards a dark steady state that entangles all atoms. The long-range resonant dipole-dipole interaction between different Rydberg states extends the entanglement beyond the van der Walls interaction range with perspectives for entangling large and distant ensembles....
Large margin classifier-based ensemble tracking
Wang, Yuru; Liu, Qiaoyuan; Yin, Minghao; Wang, ShengSheng
2016-07-01
In recent years, many studies consider visual tracking as a two-class classification problem. The key problem is to construct a classifier with sufficient accuracy in distinguishing the target from its background and sufficient generalize ability in handling new frames. However, the variable tracking conditions challenges the existing methods. The difficulty mainly comes from the confused boundary between the foreground and background. This paper handles this difficulty by generalizing the classifier's learning step. By introducing the distribution data of samples, the classifier learns more essential characteristics in discriminating the two classes. Specifically, the samples are represented in a multiscale visual model. For features with different scales, several large margin distribution machine (LDMs) with adaptive kernels are combined in a Baysian way as a strong classifier. Where, in order to improve the accuracy and generalization ability, not only the margin distance but also the sample distribution is optimized in the learning step. Comprehensive experiments are performed on several challenging video sequences, through parameter analysis and field comparison, the proposed LDM combined ensemble tracker is demonstrated to perform with sufficient accuracy and generalize ability in handling various typical tracking difficulties.
Model error estimation in ensemble data assimilation
Directory of Open Access Journals (Sweden)
S. Gillijns
2007-01-01
Full Text Available A new methodology is proposed to estimate and account for systematic model error in linear filtering as well as in nonlinear ensemble based filtering. Our results extend the work of Dee and Todling (2000 on constant bias errors to time-varying model errors. In contrast to existing methodologies, the new filter can also deal with the case where no dynamical model for the systematic error is available. In the latter case, the applicability is limited by a matrix rank condition which has to be satisfied in order for the filter to exist. The performance of the filter developed in this paper is limited by the availability and the accuracy of observations and by the variance of the stochastic model error component. The effect of these aspects on the estimation accuracy is investigated in several numerical experiments using the Lorenz (1996 model. Experimental results indicate that the availability of a dynamical model for the systematic error significantly reduces the variance of the model error estimates, but has only minor effect on the estimates of the system state. The filter is able to estimate additive model error of any type, provided that the rank condition is satisfied and that the stochastic errors and measurement errors are significantly smaller than the systematic errors. The results of this study are encouraging. However, it remains to be seen how the filter performs in more realistic applications.
Variety of synchronous regimes in neuronal ensembles
Komarov, M. A.; Osipov, G. V.; Suykens, J. A. K.
2008-09-01
We consider a Hodgkin-Huxley-type model of oscillatory activity in neurons of the snail Helix pomatia. This model has a distinctive feature: It demonstrates multistability in oscillatory and silent modes that is typical for the thalamocortical neurons. A single neuron cell can demonstrate a variety of oscillatory activity: Regular and chaotic spiking and bursting behavior. We study collective phenomena in small and large arrays of nonidentical cells coupled by models of electrical and chemical synapses. Two single elements coupled by electrical coupling show different types of synchronous behavior, in particular in-phase and antiphase synchronous regimes. In an ensemble of three inhibitory synaptically coupled elements, the phenomenon of sequential synchronous dynamics is observed. We study the synchronization phenomena in the chain of nonidentical neurons at different oscillatory behavior coupled with electrical and chemical synapses. Various regimes of phase synchronization are observed: (i) Synchronous regular and chaotic spiking; (ii) synchronous regular and chaotic bursting; and (iii) synchronous regular and chaotic bursting with different numbers of spikes inside the bursts. We detect and study the effect of collective synchronous burst generation due to the cluster formation and the oscillatory death.
General approaches in ensemble quantum computing
Indian Academy of Sciences (India)
V Vimalan; N Chandrakumar
2008-01-01
We have developed methodology for NMR quantum computing focusing on enhancing the efficiency of initialization, of logic gate implementation and of readout. Our general strategy involves the application of rotating frame pulse sequences to prepare pseudopure states and to perform logic operations. We demonstrate experimentally our methodology for both homonuclear and heteronuclear spin ensembles. On model two-spin systems, the initialization time of one of our sequences is three-fourths (in the heteronuclear case) or one-fourth (in the homonuclear case), of the typical pulsed free precession sequences, attaining the same initialization efficiency. We have implemented the logical SWAP operation in homonuclear AMX spin systems using selective isotropic mixing, reducing the duration taken to a third compared to the standard re-focused INEPT-type sequence. We introduce the 1D version for readout of the rotating frame SWAP operation, in an attempt to reduce readout time. We further demonstrate the Hadamard mode of 1D SWAP, which offers 2N-fold reduction in experiment time for a system with -working bits, attaining the same sensitivity as the standard 1D version.
Ensemble LUT classification for degraded document enhancement
Obafemi-Ajayi, Tayo; Agam, Gady; Frieder, Ophir
2008-01-01
The fast evolution of scanning and computing technologies have led to the creation of large collections of scanned paper documents. Examples of such collections include historical collections, legal depositories, medical archives, and business archives. Moreover, in many situations such as legal litigation and security investigations scanned collections are being used to facilitate systematic exploration of the data. It is almost always the case that scanned documents suffer from some form of degradation. Large degradations make documents hard to read and substantially deteriorate the performance of automated document processing systems. Enhancement of degraded document images is normally performed assuming global degradation models. When the degradation is large, global degradation models do not perform well. In contrast, we propose to estimate local degradation models and use them in enhancing degraded document images. Using a semi-automated enhancement system we have labeled a subset of the Frieder diaries collection.1 This labeled subset was then used to train an ensemble classifier. The component classifiers are based on lookup tables (LUT) in conjunction with the approximated nearest neighbor algorithm. The resulting algorithm is highly effcient. Experimental evaluation results are provided using the Frieder diaries collection.1
Group Theory for Embedded Random Matrix Ensembles
Kota, V K B
2014-01-01
Embedded random matrix ensembles are generic models for describing statistical properties of finite isolated quantum many-particle systems. For the simplest spinless fermion (or boson) systems with say $m$ fermions (or bosons) in $N$ single particle states and interacting with say $k$-body interactions, we have EGUE($k$) [embedded GUE of $k$-body interactions) with GUE embedding and the embedding algebra is $U(N)$. In this paper, using EGUE($k$) representation for a Hamiltonian that is $k$-body and an independent EGUE($t$) representation for a transition operator that is $t$-body and employing the embedding $U(N)$ algebra, finite-$N$ formulas for moments up to order four are derived, for the first time, for the transition strength densities (transition strengths multiplied by the density of states at the initial and final energies). In the asymptotic limit, these formulas reduce to those derived for the EGOE version and establish that in general bivariate transition strength densities take bivariate Gaussian ...
Emergent order in ensembles of active spinners
van Zuiden, Benjamin C.; Paulose, Jayson; Irvine, William T. M.; Bartolo, Denis; Vitelli, Vincenzo
Interacting self-propelled particles is proxy to model many living systems from cytoskeletal motors to bird flocks, while also providing a framework to investigate fundamental questions in non equilibrium statistical mechanics. A surge of recent studies have shown that self-propulsion significantly modifies the phase behavior of particles interacting via potential interactions. A prototypical example is the so-called Motility Induced Phase Separation occurring in ensembles of self-propelled hard spheres. In stark contrast, our understanding of active spinning, as opposed to self-propulsion, remains very scarce. Here, we study a system of self-spinning dimers, interacting via soft repulsive forces. Upon varying the density and activity, we observe a range of emergent phases characterized by different degrees of spatiotemporal order in the position and orientation of the dimers. Changes in bulk properties, including crystallization, melting, and freezing, are reflected in the collective motion of the particles. We rationalize our numerical findings theoretically and demonstrate some of these concepts in a active granular experiment.
Ensemble Kalman filtering with residual nudging
Luo, Xiaodong; 10.3402/tellusa.v64i0.17130
2012-01-01
Covariance inflation and localization are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/o...
Orchestrating Distributed Resource Ensembles for Petascale Science
Energy Technology Data Exchange (ETDEWEB)
Baldin, Ilya; Mandal, Anirban; Ruth, Paul; Yufeng, Xin
2014-04-24
Distributed, data-intensive computational science applications of interest to DOE scientific com- munities move large amounts of data for experiment data management, distributed analysis steps, remote visualization, and accessing scientific instruments. These applications need to orchestrate ensembles of resources from multiple resource pools and interconnect them with high-capacity multi- layered networks across multiple domains. It is highly desirable that mechanisms are designed that provide this type of resource provisioning capability to a broad class of applications. It is also important to have coherent monitoring capabilities for such complex distributed environments. In this project, we addressed these problems by designing an abstract API, enabled by novel semantic resource descriptions, for provisioning complex and heterogeneous resources from multiple providers using their native provisioning mechanisms and control planes: computational, storage, and multi-layered high-speed network domains. We used an extensible resource representation based on semantic web technologies to afford maximum flexibility to applications in specifying their needs. We evaluated the effectiveness of provisioning using representative data-intensive ap- plications. We also developed mechanisms for providing feedback about resource performance to the application, to enable closed-loop feedback control and dynamic adjustments to resource allo- cations (elasticity). This was enabled through development of a novel persistent query framework that consumes disparate sources of monitoring data, including perfSONAR, and provides scalable distribution of asynchronous notifications.
Quantum metrology with cold atomic ensembles
Directory of Open Access Journals (Sweden)
Mitchell Morgan W.
2013-08-01
Full Text Available Quantum metrology uses quantum features such as entanglement and squeezing to improve the sensitivity of quantum-limited measurements. Long established as a valuable technique in optical measurements such as gravitational-wave detection, quantum metrology is increasingly being applied to atomic instruments such as matter-wave interferometers, atomic clocks, and atomic magnetometers. Several of these new applications involve dual optical/atomic quantum systems, presenting both new challenges and new opportunities. Here we describe an optical magnetometry system that achieves both shot-noise-limited and projection-noise-limited performance, allowing study of optical magnetometry in a fully-quantum regime [1]. By near-resonant Faraday rotation probing, we demonstrate measurement-based spin squeezing in a magnetically-sensitive atomic ensemble [2-4]. The versatility of this system allows us also to design metrologically-relevant optical nonlinearities, and to perform quantum-noise-limited measurements with interacting photons. As a first interaction-based measurement [5], we implement a non-linear metrology scheme proposed by Boixo et al. with the surprising feature of precision scaling better than the 1/N “Heisenberg limit” [6].
Evaluation of seasonal ensemble forecasts in Norway
Tore Sinnes, Svein; Engeland, Kolbjørn; Langsholt, Elin; Roar Sælthun, Nils
2017-04-01
Throughout the winter and spring season, seasonal forecasts are used by the Norwegian Water Resources and Energy Directorate (NVE) in order to assess the probability for sever floods or for low seasonal runoff volumes. The latter is especially important for hydropower production. The seasonal forecasts are generated by a set of 145 lumped, elevation distributed HBV models distributed all over Norway. The observed weather is used to establish the initial snow cover, soil moisture and groundwater levels in the HBV model. Subsequently, scenarios are created by using time series of observed weather the previous 50 years, creating a total of 50 ensembles. The predictability of this seasonal forecasting system depends therefore on the importance of the initial conditions, and in Norway the seasonal snow cover is especially important. The aim of this study is to evaluate the performance of the seasonal forecasts of flood peaks and seasonal runoff volumes and especially to evaluate of the predictability depends on (i) catchment climatology and (ii) issue dates and lead times. For achieving these aims, evaluation criterions assessing reliability and sharpness were used. The results shows that the predictability is the highest for catchments where the spring runoff is dominated by snow melt. The predictability is the highest for the shortest lead times (up to 1 months ahead).The predictive performance is higher for runoff volumes than for the flood peaks.
Directory of Open Access Journals (Sweden)
G. Thirel
2010-08-01
Full Text Available The use of ensemble streamflow forecasts is developing in the international flood forecasting services. Ensemble streamflow forecast systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM hydro-meteorological suite, which initializes the ensemble streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of Météo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF 10-day Ensemble Prediction System (EPS. Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm
SuperTools Test and Evaluation Plan
Energy Technology Data Exchange (ETDEWEB)
Mannos, Tom J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Mixed Signal ASIC Design
2017-01-01
Superconducting electronics (SCE) represents a potential path to efficient exascale computing for HPC and data center applications, but SCE-based circuit design lags far behind its CMOS equivalent. IARPA’s ongoing C3 program and its developing SuperTools program aim to jumpstart SCE R&D with the near-term goal of producing a high-speed, low-energy, 64-bit RISC processor using Josephson Junction based logic cells. SuperTools performers will develop software tools for efficient SCE design and accurate simulation and characterization of JJ-based circuits, which include the RSFQ, RQL, and AQFP logic families. T&E teams from NIST, MIT Lincoln Lab, Berkeley Lab, and Sandia National Labs will evaluate the tools and fabricate test circuits to compare with simulated results. The five-year, three-phase program includes 48 performer deliverables, three annual technical exchange meetings, and annual site visits.
Italian super-eruption larger than thought
Schultz, Colin
2012-07-01
Recent research suggested that the super-eruption of the Campi Flegrei caldera volcano in southern Italy about 40,000 years ago may have played a part in wiping out, or forcing the migration of, the Neanderthal and modern human populations in the eastern Mediterranean regions that were covered in ash. Now a new modeling study by Costa et al. suggests that this eruption may have been even larger than previously thought. This Campi Flegrei eruption produced a widespread ash layer known as Campanian Ignimbrite (CI). Using ash thickness measurements collected at 115 sites and a three-dimensional ash dispersal model, the researchers found that the CI super-eruption would have spread 250-300 cubic kilometers of ash across a 3.7-million-square kilometer region—2 to 3 times previous ash volume estimates.
Optical super-resolution microscopy in neurobiology.
Sigrist, Stephan J; Sabatini, Bernardo L
2012-02-01
Understanding the highly plastic nature of neurons requires the dynamic visualization of their molecular and cellular organization in a native context. However, due to the limited resolution of standard light microscopy, many of the structural specializations of neurons cannot be resolved. A recent revolution in light microscopy has given rise to several super-resolution light microscopy methods yielding 2-10-fold higher resolution than conventional microscopy. We here describe the principles behind these techniques as well as their application to the analysis of the molecular architecture of the synapse. Furthermore, we discuss the potential for continued development of super-resolution microscopy as necessary for live imaging of neuronal structure and function in the brain.
Super-resolution microscopy: a comparative treatment.
Kasuboski, James M; Sigal, Yury J; Joens, Matthew S; Lillemeier, Bjorn F; Fitzpatrick, James A J
2012-10-01
One of the fundamental limitations of optical microscopy is that of diffraction, or in essence, how small a beam of light can be focused by using an optical lens system. This constraint, or barrier if you will, was theoretically described by Ernst Abbe in 1873 and is roughly equal to half the wavelength of light used to probe the system. Many structures, particularly those within cells, are much smaller than this limit and thus are difficult to visualize. Over the last two decades, a new field of super-resolution imaging has been created and been developed into a broad range of techniques that allow routine imaging beyond the far-field diffraction limit of light. In this unit we outline the basic principles of the various super-resolution imaging modalities, paying particular attention to the technical considerations for biological imaging. Furthermore, we discuss their various applications in the imaging of both fixed and live biological samples.
(Super-)renormalizably dressed black holes
Ayón-Beato, Eloy; Méndez-Zavaleta, Julio A
2015-01-01
Black holes supported by self-interacting conformal scalar fields can be considered as renormalizably dressed since the conformal potential is nothing but the top power-counting renormalizable self-interaction in the relevant dimension. On the other hand, potentials defined by powers which are lower than the conformal one are also phenomenologically relevant since they are in fact super-renormalizable. In this work we provide a new map that allows to build black holes dressed with all the (super-)renormalizable contributions starting from known conformal seeds. We explicitly construct several new examples of these solutions in dimensions $D=3$ and $D=4$, including not only stationary configurations but also time-dependent ones.
Super/subradiant second harmonic generation
Koganov, Gennady A.; Shuker, Reuben
2017-04-01
A scheme for active second harmonics generation is suggested. The system comprises N three-level atoms in ladder configuration, situated into a resonant cavity. The system generates the field whose frequency is twice the frequency of the pumping laser, and the field phase is locked to the phase of the pumping field. It is found that the system can lase in either superradiant or subradiant regime, depending on the number of atoms N. When N passes some critical value the transition from the super to subradiance occurs in a phase-transition-like manner. Stability study of the steady state supports this conclusion. For experimental realization of the super/subradiant second harmonics generation we propose semiconductor quantum well structures, superconducting quantum circuits, and evanescently coupled waveguides in which equally spaced levels relevant to this study exist.
Directory of Open Access Journals (Sweden)
Holdsworth Daniel L.
2017-01-01
Full Text Available SuperWASP is one of the largest ground-based surveys for transiting exoplanets. To date, it has observed over 31 million stars. Such an extensive database of time resolved photometry holds the potential for extensive searches of stellar variability, and provide solid candidates for the upcoming TESS mission. Previous work by e.g. [15], [5], [12] has shown that the WASP archive provides a wealth of pulsationally variable stars. In this talk I will provide an overview of the SuperWASP project, present some of the published results from the survey, and some of the on-going work to identify key targets for the TESS mission.
Robust super-resolution without regularization
Energy Technology Data Exchange (ETDEWEB)
Pham, T Q [Canon Information Systems Research Australia, 1 Thomas Holt drive, North Ryde, NSW 2113 (Australia); Vliet, L J v [Quantitative Imaging Group, Department of Imaging Science and Technology, Faculty of Applied Sciences, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft (Netherlands); Schutte, K [Electro-Optics Group, TNO Defence, Security and Safety, PO Box 96864, 2509 JG The Hague (Netherlands)
2008-07-15
Super-resolution restoration is the problem of restoring a high-resolution scene from multiple degraded low-resolution images under motion. Due to imaging blur and noise, this problem is ill-posed. Additional constraints such as smoothness of the solution (i.e. regularization) is often required to obtain a stable solution. While regularizing the cost function is a standard practice in image restoration, we propose a restoration algorithm that does not require this extra regularization term. The robustness of the algorithm is achieved by a robust error norm that does not response to intensity outliers. With the outliers suppressed, our solution behaves similarly to a maximum-likelihood solution under the presence of Gaussian noise. The effectiveness of our algorithm is demonstrated with super-resolution restoration of real infrared image sequences under severe aliasing and intensity outliers.
Penrose Pixels for Super-Resolution.
Ben-Ezra, M; Lin, Zhouchen; Wilburn, Bennett; Zhang, Wei
2011-07-01
We present a novel approach to reconstruction-based super-resolution that uses aperiodic pixel tilings, such as a Penrose tiling or a biological retina, for improved performance. To this aim, we develop a new variant of the well-known error back projection super-resolution algorithm that makes use of the exact detector model in its back projection operator for better accuracy. Pixels in our model can vary in shape and size, and there may be gaps between adjacent pixels. The algorithm applies equally well to periodic or aperiodic pixel tilings. We present analysis and extensive tests using synthetic and real images to show that our approach using aperiodic layouts substantially outperforms existing reconstruction-based algorithms for regular pixel arrays. We close with a discussion of the feasibility of manufacturing CMOS or CCD chips with pixels arranged in Penrose tilings.
Temporal super resolution using variational methods
DEFF Research Database (Denmark)
Keller, Sune Høgild; Lauze, Francois Bernard; Nielsen, Mads
2010-01-01
and intensities are calculated simultaneously in a multiresolution setting. A frame doubling version of our algorithm is implemented and in testing it, we focus on making the motion of high contrast edges to seem smooth and thus reestablish the illusion of motion pictures.......Temporal super resolution (TSR) is the ability to convert video from one frame rate to another and is as such a key functionality in modern video processing systems. A higher frame rate than what is recorded is desired for high frame rate displays, for super slow-motion, and for video/film format...... conversion (where also lower frame rates than recorded is sometimes required). We discuss and detail the requirements imposed by the human visual system (HVS) on TSR algorithms, of which the need for (apparent) fluid motion, also known as the phi-effect, is the principal one. This problem is typically...
Infinite ensemble of support vector machines for prediction of ...
African Journals Online (AJOL)
user
Many researchers have demonstrated the use of artificial neural networks (ANNs) to ..... Following section discusses the effect of infinite ensemble approach ..... major problem with artificial intelligence-based modeling approaches is their ...
An educational model for ensemble streamflow simulation and uncertainty analysis
Directory of Open Access Journals (Sweden)
A. AghaKouchak
2012-06-01
Full Text Available This paper presents a hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this model, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The model includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for not only hydrological processes, but also for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity.
Relation between native ensembles and experimental structures of proteins
DEFF Research Database (Denmark)
Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.
2006-01-01
Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest......Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... heterogeneity of the native state in solution. We find that different NMR measurements probing structure and dynamics of given proteins in solution, including order parameters, scalar couplings, and residual dipolar couplings, are remarkably well reproduced by their respective high-sequence similarity Protein...
Spectroscopic properties of inhomogeneously broadened spin ensembles in a cavity
DEFF Research Database (Denmark)
Kurucz, Zoltan; Wesenberg, Janus; Mølmer, Klaus
2011-01-01
The enhanced collective coupling to weak quantum fields may turn atomic or spin ensembles into an important component in quantum information processing architectures. Inhomogeneous broadening can, however, significantly reduce the coupling and the lifetime of the collective excitation...
Trace formula for an ensemble of bumpy billiards
Pavloff, N
1995-01-01
We study the semiclassical quantization of an ensemble of billiards with a small random shape deformation. We derive a trace formula averaged over shape disorder. The results are illustrated by the study of supershells in rough metal clusters.
Time and ensemble averaging in time series analysis
Latka, Miroslaw; Jernajczyk, Wojciech; West, Bruce J
2010-01-01
In many applications expectation values are calculated by partitioning a single experimental time series into an ensemble of data segments of equal length. Such single trajectory ensemble (STE) is a counterpart to a multiple trajectory ensemble (MTE) used whenever independent measurements or realizations of a stochastic process are available. The equivalence of STE and MTE for stationary systems was postulated by Wang and Uhlenbeck in their classic paper on Brownian motion (Rev. Mod. Phys. 17, 323 (1945)) but surprisingly has not yet been proved. Using the stationary and ergodic paradigm of statistical physics -- the Ornstein-Uhlenbeck (OU) Langevin equation, we revisit Wang and Uhlenbeck's postulate. In particular, we find that the variance of the solution of this equation is different for these two ensembles. While the variance calculated using the MTE quantifies the spreading of independent trajectories originating from the same initial point, the variance for STE measures the spreading of two correlated r...
Phase-selective entrainment of nonlinear oscillator ensembles
Zlotnik, Anatoly; Nagao, Raphael; Kiss, István Z.; Li-Shin, Jr.
2016-03-01
The ability to organize and finely manipulate the hierarchy and timing of dynamic processes is important for understanding and influencing brain functions, sleep and metabolic cycles, and many other natural phenomena. However, establishing spatiotemporal structures in biological oscillator ensembles is a challenging task that requires controlling large collections of complex nonlinear dynamical units. In this report, we present a method to design entrainment signals that create stable phase patterns in ensembles of heterogeneous nonlinear oscillators without using state feedback information. We demonstrate the approach using experiments with electrochemical reactions on multielectrode arrays, in which we selectively assign ensemble subgroups into spatiotemporal patterns with multiple phase clusters. The experimentally confirmed mechanism elucidates the connection between the phases and natural frequencies of a collection of dynamical elements, the spatial and temporal information that is encoded within this ensemble, and how external signals can be used to retrieve this information.
Ensembles on configuration space classical, quantum, and beyond
Hall, Michael J W
2016-01-01
This book describes a promising approach to problems in the foundations of quantum mechanics, including the measurement problem. The dynamics of ensembles on configuration space is shown here to be a valuable tool for unifying the formalisms of classical and quantum mechanics, for deriving and extending the latter in various ways, and for addressing the quantum measurement problem. A description of physical systems by means of ensembles on configuration space can be introduced at a very fundamental level: the basic building blocks are a configuration space, probabilities, and Hamiltonian equations of motion for the probabilities. The formalism can describe both classical and quantum systems, and their thermodynamics, with the main difference being the choice of ensemble Hamiltonian. Furthermore, there is a natural way of introducing ensemble Hamiltonians that describe the evolution of hybrid systems; i.e., interacting systems that have distinct classical and quantum sectors, allowing for consistent descriptio...
Ensemble vs. time averages in financial time series analysis
Seemann, Lars; Hua, Jia-Chen; McCauley, Joseph L.; Gunaratne, Gemunu H.
2012-12-01
Empirical analysis of financial time series suggests that the underlying stochastic dynamics are not only non-stationary, but also exhibit non-stationary increments. However, financial time series are commonly analyzed using the sliding interval technique that assumes stationary increments. We propose an alternative approach that is based on an ensemble over trading days. To determine the effects of time averaging techniques on analysis outcomes, we create an intraday activity model that exhibits periodic variable diffusion dynamics and we assess the model data using both ensemble and time averaging techniques. We find that ensemble averaging techniques detect the underlying dynamics correctly, whereas sliding intervals approaches fail. As many traded assets exhibit characteristic intraday volatility patterns, our work implies that ensemble averages approaches will yield new insight into the study of financial markets’ dynamics.
Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.
Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel
2017-06-01
Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.
Institute of Scientific and Technical Information of China (English)
韦少雯
2006-01-01
Super-pharm，这家可直译为“超级药店”的以色列最大的药品、化妆品及个人护理品零售企业，是由全球排名前几十位的亿万富翁、犹太人Murray Koffler创立的家族企业。
Super Resolution Imaging Applied to Scientific Images
2007-05-01
investigator, (3) development of Papoulis -Gerchberg method to implement the analytic continuation of spectral details, (4) exploration of contourlet and...off with noise present in the observation. In [30] we make use of Papoulis -Gerchberg algorithm of signal extrapolation to perform Image super...we have used a training database consisting of high resolution images. For Papoulis -Gerchberg method number of iterations and the filter used both
The SuperNova Early Warning System
Scholberg, K.
2008-01-01
A core collapse in the Milky Way will produce an enormous burst of neutrinos in detectors world-wide. Such a burst has the potential to provide an early warning of a supernova's appearance. I will describe the nature of the signal, the sensitivity of current detectors, and SNEWS, the SuperNova Early Warning System, a network designed to alert astronomers as soon as possible after the detected neutrino signal.
(Super-)renormalizably dressed black holes
Ayón-Beato, Eloy; Hassaïne, Mokhtar; Méndez-Zavaleta, Julio A.
2015-01-01
Black holes supported by self-interacting conformal scalar fields can be considered as renormalizably dressed since the conformal potential is nothing but the top power-counting renormalizable self-interaction in the relevant dimension. On the other hand, potentials defined by powers which are lower than the conformal one are also phenomenologically relevant since they are in fact super-renormalizable. In this work we provide a new map that allows to build black holes dressed with all the (su...
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
担心情人节没人陪？还在幻想能与谁约会？2009年2月14日，梦想照进现实，SJ-M将在上海举办“情人Superman-Super Junior-M 2009上海歌会”，化身你的甜蜜情人，与你一起共度浪漫情人节。
Super-Kamiokande - Present and Future
Energy Technology Data Exchange (ETDEWEB)
Suzuki, Y. [Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Higashi-Mozumi, Kamioka-chou, Hida-city, Gifu 506-1205 (Japan)
2004-12-15
We summarize the latest results on the atmospheric and solar neutrinos from Super-Kamiokande. The atmospheric neutrino oscillation analyses with two flavors and with three flavor are discussed and the new results based on the L/E analysis are shown. New solar neutrino results based on the un-binned method is discussed. The current status of SK-II and the future prospects for SK neutrino oscillation experiment are summarized.
The (Super)String Theories' Problems
Naboulsi, R
2003-01-01
(Super)String theories are theoretical ideas that go beyond the standard model of particle and high energy physics and show promise for unifying all forces in nature including the gravitational one. In this unification a prominent role is played by the duality symmetries which relate different theories. I present a review of these developements and discuss their problems and possible impact in low-energy physics. We explain and discuss some ideas concerning string field theories from noncommutative geometry.
T-Duality from super Lie n-algebra cocycles for super p-branes
Fiorenza, Domenico; Schreiber, Urs
2016-01-01
We compute the $L_\\infty$-theoretic dimensional reduction of the F1/D$p$-brane super $L_\\infty$-cocycles with coefficients in rationalized twisted K-theory from the 10d type IIA and type IIB super Lie algebras down to 9d. We show that the two resulting coefficient $L_\\infty$-algebras are naturally related by an $L_\\infty$-isomorphism which we find to act on the super $p$-brane cocycles by the infinitesimal version of the rules of topological T-duality and inducing an isomorphism between $K^0$ and $K^1$, rationally. Moreover, we show that these $L_\\infty$-algebras are the homotopy quotients of the RR-charge coefficients by the "T-duality Lie 2-algebra". We find that the induced $L_\\infty$-extension is a gerby extension of a 9+(1+1) dimensional (i.e. "doubled") T-duality correspondence super-spacetime, which serves as a local model for T-folds. We observe that this still extends, via the D0-brane cocycle of its type IIA factor, to a 10+(1+1)-dimensional super Lie algebra. Finally we observe that this satisfies ...
An automated approach to network features of protein structure ensembles.
Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi
2013-10-01
Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.
Clustering Categorical Data:A Cluster Ensemble Approach
Institute of Scientific and Technical Information of China (English)
He Zengyou(何增友); Xu Xiaofei; Deng Shengchun
2003-01-01
Clustering categorical data, an integral part of data mining,has attracted much attention recently. In this paper, the authors formally define the categorical data clustering problem as an optimization problem from the viewpoint of cluster ensemble, and apply cluster ensemble approach for clustering categorical data. Experimental results on real datasets show that better clustering accuracy can be obtained by comparing with existing categorical data clustering algorithms.
Ensemble control of linear systems with parameter uncertainties
Kou, Kit Ian; Liu, Yang; Zhang, Dandan; Tu, Yanshuai
2016-07-01
In this paper, we study the optimal control problem for a class of four-dimensional linear systems based on quaternionic and Fourier analysis. When the control is unconstrained, the optimal ensemble controller for this linear ensemble control systems is given in terms of prolate spheroidal wave functions. For the constrained convex optimisation problem of such systems, the quadratic programming is presented to obtain the optimal control laws. Simulations are given to verity the effectiveness of the proposed theory.
Pycobra: A Python Toolbox for Ensemble Learning and Visualisation
Guedj, Benjamin; Srinivasa Desikan, Bhargav
2017-01-01
We introduce \\texttt{pycobra}, a Python library devoted to ensemble learning (regression and classification) and visualisation. Its main assets are the implementation of several ensemble learning algorithms, a flexible and generic interface to compare and blend any existing machine learning algorithm available in Python libraries (as long as a \\texttt{predict} method is given), and visualisation tools such as Voronoi tessellations. \\texttt{pycobra} is fully \\texttt{scikit-learn} compatible an...
Ensembles of probability estimation trees for customer churn prediction
2010-01-01
Customer churn prediction is one of the most, important elements tents of a company's Customer Relationship Management, (CRM) strategy In tins study, two strategies are investigated to increase the lift. performance of ensemble classification models, i.e (1) using probability estimation trees (PETs) instead of standard decision trees as base classifiers; and (n) implementing alternative fusion rules based on lift weights lot the combination of ensemble member's outputs Experiments ale conduct...
SuperB Progress Reports - Physics
O'Leary, B.; Ramon, M.; Pous, E.; De Fazio, F.; Palano, A.; Eigen, G.; Asgeirsson, D.; Cheng, C.H.; Chivukula, A.; Echenard, B.; Hitlin, D.G.; Porter, F.; Rakitin, A.; Heinemeyer, S.; McElrath, B.; Andreassen, R.; Meadows, B.; Sokoloff, M.; Blanke, M.; Lesiak, T.; Shindou, T.; Ronga, F.; Baldini, W.; Bettoni, D.; Calabrese, R.; Cibinetto, G.; Luppi, E.; Rama, M.; Bossi, F.; Guido, E.; Patrignani, C.; Tosi, S.; Davies, C.; Lunghi, E.; Haisch, U.; Hurth, T.; Westhoff, S.; Crivellin, A.; Hofer, L.; Goto, T.; Brown, David Nathan; Branco, G.C.; Zupan, J.; Herrero, M.; Rodriguez-Sanchez, A.; Simi, G.; Tackmann, F.J.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Lindemann, D.M.; Robertson, S.H.; Duling, B.; Gemmler, K.; Gorbahn, M.; Jager, S.; Paradisi, P.; Straub, D.M.; Bigi, I.; Asner, D.M.; Fast, J.E.; Kouzes, R.T.; Morandin, M.; Rotondo, M.; Ben-Haim, E.; Arnaud, N.; Burmistrov, L.; Kou, E.; Perez, A.; Stocchi, A.; Viaud, B.; Domingo, F.; Piccinini, F.; Manoni, E.; Batignani, G.; Cervelli, A.; Forti, F.; Giorgi, M.; Lusiani, A.; Oberhof, B.; Paoloni, E.; Neri, N.; Walsh, J.; Bevan, A.; Bona, M.; Walker, C.; Weiland, C.; Lenz, A.; Gonzalez-Sprinberg, G.; Faccini, R.; Renga, F.; Polosa, A.; Silvestrini, L.; Virto, J.; Ciuchini, M.; Lubicz, V.; Tarantino, C.; Wilson, F.F.; Carpinelli, M.; Huber, T.; Mannel, T.; Graham, M.; Ratcliff, B.N.; Santoro, V.; Sekula, S.; Shougaev, K.; Soffer, A.; Shimizu, Y.; Gambino, P.; Mussa, R.; Nardecchia, M.; Stal, O.; Bernabeu, J.; Botella, F.; Jung, M.; Lopez March, N.; Martinez Vidal, F.; Oyanguren, A.; Pich, A.; Lozano, M.A.Sanchis; Vidal, J.; Vives, O.; Banerjee, S.; Roney, J.M.; Petrov, A.A.; Flood, K.
2010-01-01
SuperB is a high luminosity e+e- collider that will be able to indirectly probe new physics at energy scales far beyond the reach of any man made accelerator planned or in existence. Just as detailed understanding of the Standard Model of particle physics was developed from stringent constraints imposed by flavour changing processes between quarks, the detailed structure of any new physics is severely constrained by flavour processes. In order to elucidate this structure it is necessary to perform a number of complementary studies of a set of golden channels. With these measurements in hand, the pattern of deviations from the Standard Model behavior can be used as a test of the structure of new physics. If new physics is found at the LHC, then the many golden measurements from SuperB will help decode the subtle nature of the new physics. However if no new particles are found at the LHC, SuperB will be able to search for new physics at energy scales up to 10-100 TeV. In either scenario, flavour physics measure...
Super Marx Generator for Thermonuclear Ignition
Winterberg, Friedwardt
2008-01-01
In ongoing electric pulse power driven inertial confinement fusion experiments, Marx generators are connected in parallel with the target in the center of a ring of the Marx generators. There the currents, not the voltages add up. Instead of connecting a bank of Marx generator in parallel, one may connect them in series, adding up their voltages, not the currents. If, for example, fifty 20 MV Marx generators are connected in series, they would add up to a gigavolt. But to prevent breakdown, the adding up of the voltages in such a super-Marx generator must be fast. For this reason, it is proposed that each of the Marx generators charges up a fast discharge capacitor, with the thusly charged fast capacitors becoming the elements of a second stage super Marx generator. In a super Marx generator, the Marx generators also assume the role of the resistors in the original Marx circuit. With a voltage of 10^9 Volt and a discharge current of 10^7 Ampere, the generation of a 10^16 Watt GeV proton beam becomes possible,...
The SuperNEMO tracking detector
Cascella, M
2015-01-01
The SuperNEMO detector will search for neutrinoless double beta decay at the Modane Underground Laboratory on the French-Italian border. This decay mode, if observed, would be proof that the neutrino is its own antiparticle, would constitute evidence for total lepton number violation, and could allow a measurement of the absolute neutrino mass. The SuperNEMO experiment is designed to reach a half-life sensitivity of $10^{26}$ years corresponding to an effective Majorana neutrino mass of $50-100~$meV. The SuperNEMO detector design allows complete topological reconstruction of the double beta decay event enabling excellent levels of background rejection. In the event of a discovery, such topological measurements will be vital in determining the nature of the lepton number violating process. This reconstruction will be performed by a gaseous tracking detector, consisting of 2034 drift cells per module operated in Geiger mode. The tracker of the Demonstrator Module is currently under construction in the UK. This ...
SuperB Technical Design Report
Baszczyk, M; Kolodziej, J; Kucewicz, W; Sapor, M; Jeremie, A; Pous, E Grauges; Bruno, G E; De Robertis, G; Diacono, D; Donvito, G; Fusco, P; Gargano, F; Giordano, F; Loddo, F; Loparco, F; Maggi, G P; Manzari, V; Mazziotta, M N; Nappi, E; Palano, A; Santeramo, B; Sgura, I; Silvestris, L; Spinoso, V; Eigen, G; Zalieckas, J; Zhuo, Z; Jenkovszky, L; Balbi, G; Boldini, M; Bonacorsi, D; Cafaro, V; D'Antone, I; Dallavalle, G M; Di Sipio, R; Fabbri, F; Fabbri, L; Gabrielli, A; Galli, D; Giacomelli, P; Giordano, V; Giorgi, F M; Grandi, C; Lax, I; Meo, S Lo; Marconi, U; Montanari, A; Pellegrini, G; Piccinini, M; Rovelli, T; Cesari, N Semprini; Torromeo, G; Tosi, N; Travaglini, R; Vagnoni, V M; Valentinetti, S; Villa, M; Zoccoli, A; Caron, J -F; Hearty, C; Lu, P F -T; Mattison, T S; McKenna, J A; So, R Y -C; Barnyakov, M Yu; Blinov, V E; Botov, A A; Druzhinin, V P; Golubev, V B; Kononov, S A; Kravchenko, E A; Levichev, E B; Onuchin, A P; Serednyakov, S I; Shtol, D A; Skovpen, Y I; Solodov, E P; Cardini, A; Carpinelli, M; Chao, D S -T; Cheng, C H; Doll, D A; Echenard, B; Flood, K; Hanson, J; Hitlin, D G; Ongmongkolkul, P; Porter, F C; Zhu, R Y; Randazzo, N; Burelo, E De La Cruz; Zheng, Y; Campos, P; De Silva, M; Kathirgamaraju, A; Meadows, B; Pushpawela, B; Shi, Y; Sokoloff, M; Castro, G Lopez; Ciaschini, V; Franchini, P; Giacomini, F; Paolini, A; Polania, G A Calderon; Laczek, S; Romanowicz, P; Szybinski, B; Czuchry, M; Flis, L; Harezlak, D; Kocot, J; Radecki, M; Sterzel, M; Szepieniec, T; Szymocha, T; Wójcik, P; Andreotti, M; Baldini, W; Calabrese, R; Carassiti, V; Cibinetto, G; Ramusino, A Cotta; Evangelisti, F; Gianoli, A; Luppi, E; Malaguti, R; Manzali, M; Melchiorri, M; Munerato, M; Padoan, C; Santoro, V; Tomassetti, L; Beretta, M M; Biagini, M; Boscolo, M; Capitolo, E; de Sangro, R; Esposito, M; Felici, G; Finocchiaro, G; Gatta, M; Gatti, C; Guiducci, S; Lauciani, S; Patteri, P; Peruzzi, I; Piccolo, M; Raimondi, P; Rama, M; Sanelli, C; Tomassini, S; Fabbricatore, P; Delepine, D; Santos, M A Reyes; Chrzaszcz, M; Grzymkowski, R; Knap, P; Kotula, J; Lesiak, T; Ludwin, J; Michalowski, J; Pawlik, B; Rachwal, B; Stodulski, M; Wiechczynski, J; Witek, M; Zawiejski, L; Zdybal, M; Aushev, V Y; Ustynov, A; Arnaud, N; Bambade, P; Beigbeder, C; Bogard, F; Borsato, M; Breton, D; Brossard, J; Burmistrov, L; Charlet, D; Chaumat, V; Dadoun, O; Berni, M El; Maalmi, J; Puill, V; Rimbault, C; Stocchi, A; Tocut, V; Variola, A; Wallon, S; Wormser, G; Grancagnolo, F; Ben-Haim, E; Sitt, S; Baylac, M; Bourrion, O; Deconto, J -M; Martinez, Y Gomez; Monseu, N; Muraz, J -F; Real, J -S; Vescovi, C; Cenci, R; Jawahery, A; Roberts, D; Twedt, E W; Cheaib, R; Lindemann, D; Nderitu, S; Patel, P; Robertson, S H; Swersky, D; Warburton, A; Flores, E Cuautle; Sanchez, G Toledo; Biassoni, P; Bombelli, L; Citterio, M; Coelli, S; Fiorini, C; Liberali, V; Monti, M; Nasri, B; Neri, N; Palombo, F; Sabatini, F; Stabile, A; Berra, A; Giachero, A; Gotti, C; Lietti, D; Maino, M; Pessina, G; Prest, M; Martin, J -P; Simard, M; Starinski, N; Taras, P; Drutskoy, A; Makarychev, S; Nefediev, A V; Aloisio, A; Cavaliere, S; De Nardo, G; Della Pietra, M; Doria, A; Giordano, R; Ordine, A; Pardi, S; Russo, G; Sciacca, C; Bigi, I I; Jessop, C P; Wang, W; Bellato, M; Benettoni, M; Corvo, M; Crescente, A; Corso, F Dal; Dosselli, U; Fanin, C; Gianelle, A; Longo, S; Michelotto, M; Montecassiano, F; Morandin, M; Pengo, R; Posocco, M; Rotondo, M; Simi, G; Stroili, R; Gaioni, L; Manazza, A; Manghisoni, M; Ratti, L; Re, V; Traversi, G; Zucca, S; Bizzaglia, S; Bizzarri, M; Cecchi, C; Germani, S; Lebeau, M; Lubrano, P; Manoni, E; Papi, A; Rossi, A; Scolieri, G; Batignani, G; Bettarini, S; Casarosa, G; Cervelli, A; Fella, A; Forti, F; Giorgi, M; Lilli, L; Lusiani, A; Oberhof, B; Paladino, A; Pantaleo, F; Paoloni, E; Perez, A L Perez; Rizzo, G; Walsh, J; Téllez, A Fernández; Beck, G; Berman, M; Bevan, A; Gannaway, F; Inguglia, G; Martin, A J; Morris, J; Bocci, V; Capodiferro, M; Chiodi, G; Dafinei, I; Drenska, N V; Faccini, R; Ferroni, F; Gargiulo, C; Gauzzi, P; Luci, C; Lunadei, R; Martellotti, G; Pellegrino, F; Pettinacci, V; Pinci, D; Recchia, L; Ruggeri, D; Zullo, A; Camarri, P; Cardarelli, R; De Santis, C; Di Ciaccio, A; Di Felice, V; Di Palma, F; Di Simone, A; Marcelli, L; Messi, R; Moricciani, D; Sparvoli, R; Tammaro, S; Branchini, P; Budano, A; Bussino, S; Ciuchini, M; Nguyen, F; Passeri, A; Ruggieri, F; Spiriti, E; Wilson, F; Monzon, I Leon; Millan-Almaraz, J R; Podesta-Lerma, P L M; Aston, D; Dey, B; Fisher, A; Jackson, P D; Leith, D W G S; Luitz, S; MacFarlane, D; McCulloch, M; Metcalfe, S; Novokhatski, A; Osier, S; Prepost, R; Ratcliff, B; Seeman, J; Sullivan, M; Va'vra, J; Wienands, U; Wisniewski, W; Altschul, B D; Purohit, M V; Baudot, J; Ripp-Baudot, I; Cirrone, G A P; Cuttone, G; Bezshyyko, O; Dolinska, G; Soffer, A; Bianchi, F; De Mori, F; Filippi, A; Gamba, D; Marcello, S; Bomben, M; Bosisio, L; Cristaudo, P; Lanceri, L; Liberti, B; Rashevskaya, I; Stella, C; Vallazza, E S; Vitale, L; Auriemma, G; Satriano, C; Vidal, F Martinez; de Cos, J Mazorra; Oyanguren, A; Valls, P Ruiz; Beaulieu, A; Dejong, S; Franta, J; Lewczuk, M J; Roney, M; Sobie, R
2013-01-01
In this Technical Design Report (TDR) we describe the SuperB detector that was to be installed on the SuperB e+e- high luminosity collider. The SuperB asymmetric collider, which was to be constructed on the Tor Vergata campus near the INFN Frascati National Laboratory, was designed to operate both at the Upsilon(4S) center-of-mass energy with a luminosity of 10^{36} cm^{-2}s^{-1} and at the tau/charm production threshold with a luminosity of 10^{35} cm^{-2}s^{-1}. This high luminosity, producing a data sample about a factor 100 larger than present B Factories, would allow investigation of new physics effects in rare decays, CP Violation and Lepton Flavour Violation. This document details the detector design presented in the Conceptual Design Report (CDR) in 2007. The R&D and engineering studies performed to arrive at the full detector design are described, and an updated cost estimate is presented. A combination of a more realistic cost estimates and the unavailability of funds due of the global economic ...
Predicting the occurrence of super-storms
Directory of Open Access Journals (Sweden)
N. Srivastava
2005-11-01
Full Text Available A comparative study of five super-storms (D_{st}<-300 nT of the current solar cycle after the launch of SoHO, to identify solar and interplanetary variables that influence the magnitude of resulting geomagnetic storms, is described. Amongst solar variables, the initial speed of a CME is considered the most reliable predictor of the strength of the associated geomagnetic storm because fast mass ejections are responsible for building up the ram pressure at the Earth's magnetosphere. However, although most of the super-storms studied were associated with high speed CMEs, the D_{st} index of the resulting geomagnetic storms varied between -300 to -472 nT. The most intense storm of 20 November 2003, (D_{st} ~ -472 nT had its source in a comparatively smaller active region and was associated with a relatively weaker, M-class flare while all other super-storms had their origins in large active regions and were associated with strong X-class flares. However, this superstorm did not show any associated extraordinary solar and interplanetary characteristics. The study also reveals the challenge in the reliable prediction of the magnitude of a geomagnetic storm from solar and interplanetary variables.
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
Chen, Huanhuan; Yao, Xin
Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal testing. This paper describes a novel machine learning ensemble approach to building an in silico model for the prediction of the Ames test mutagenicity, one of a battery of the most commonly used experimental in vitro and in vivo genotoxicity tests for safety evaluation of chemicals. Evolutionary random neural ensemble with negative correlation learning (ERNE) [1] was developed based on neural networks and evolutionary algorithms. ERNE combines the method of bootstrap sampling on training data with the method of random subspace feature selection to ensure diversity in creating individuals within an initial ensemble. Furthermore, while evolving individuals within the ensemble, it makes use of the negative correlation learning, enabling individual NNs to be trained as accurate as possible while still manage to maintain them as diverse as possible. Therefore, the resulting individuals in the final ensemble are capable of cooperating collectively to achieve better generalization of prediction. The empirical experiment suggest that ERNE is an effective ensemble approach for predicting the Ames test mutagenicity of chemicals.
SVM and SVM Ensembles in Breast Cancer Prediction
Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong
2017-01-01
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers. PMID:28060807
Monthly Ensembles in Algal Bloom Predictions on the Baltic Sea
Roiha, Petra; Westerlund, Antti; Stipa, Tapani
2010-05-01
In this work we explore the statistical features of monthly ensembles and their capability to predict biogeochemical conditions in the Baltic Sea. Operational marine environmental modelling has been considered hard, and consequently there are very few operational ecological models. Operational modelling of harmful algal blooms is harder still, since it is difficult to separate the algal species in models, and in general, very little is known of HAB properties. We present results of an ensemble approach to HAB forecasting in the Baltic, and discuss the applicability of the forecasting method to biochemical modelling. It turns out that HABs are indeed possible to forecast with useful accuracy. For modelling the algal blooms in Baltic Sea we used FMI operational 3-dimensional biogeochemical model to produce seasonal ensemble forecasts for different physical, chemical and biological variables. The modelled variables were temperature, salinity, velocity, silicate, phosphate, nitrate, diatoms, flagellates and two species of potentially toxic filamentous cyanobacteria nodularia spumigena and aphanizomenon flos-aquae. In this work we concentrate to the latter two. Ensembles were produced by running the biogeochemical model several times and forcing it on every run with different set of seasonal weather parameters from ECMWF's mathematically perturbed ensemble prediction forecasts. The ensembles were then analysed by statistical methods and the median, quartiles, minimum and maximum values were calculated for estimating the probable amounts of algae. Validation for the forecast method was made by comparing the final results against available and valid in-situ HAB data.
SVM and SVM Ensembles in Breast Cancer Prediction.
Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong
2017-01-01
Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.
Selecting, weeding, and weighting biased climate model ensembles
Jackson, C. S.; Picton, J.; Huerta, G.; Nosedal Sanchez, A.
2012-12-01
In the Bayesian formulation, the "log-likelihood" is a test statistic for selecting, weeding, or weighting climate model ensembles with observational data. This statistic has the potential to synthesize the physical and data constraints on quantities of interest. One of the thorny issues for formulating the log-likelihood is how one should account for biases. While in the past we have included a generic discrepancy term, not all biases affect predictions of quantities of interest. We make use of a 165-member ensemble CAM3.1/slab ocean climate models with different parameter settings to think through the issues that are involved with predicting each model's sensitivity to greenhouse gas forcing given what can be observed from the base state. In particular we use multivariate empirical orthogonal functions to decompose the differences that exist among this ensemble to discover what fields and regions matter to the model's sensitivity. We find that the differences that matter are a small fraction of the total discrepancy. Moreover, weighting members of the ensemble using this knowledge does a relatively poor job of adjusting the ensemble mean toward the known answer. This points out the shortcomings of using weights to correct for biases in climate model ensembles created by a selection process that does not emphasize the priorities of your log-likelihood.
Genetic Programming Based Ensemble System for Microarray Data Classification
Directory of Open Access Journals (Sweden)
Kun-Hong Liu
2015-01-01
Full Text Available Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP based new ensemble system (named GPES, which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.
Knowledge based cluster ensemble for cancer discovery from biomolecular data.
Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying
2011-06-01
The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.
Hybrid Intrusion Detection Using Ensemble of Classification Methods
Directory of Open Access Journals (Sweden)
M.Govindarajan
2014-01-01
Full Text Available One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed for homogeneous ensemble classifiers using bagging and heterogeneous ensemble classifiers using arcing classifier and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF and Support Vector Machine (SVM as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of real and benchmark data sets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase and combining phase. A wide range of comparative experiments are conducted for real and benchmark data sets of intrusion detection. The accuracy of base classifiers is compared with homogeneous and heterogeneous models for data mining problem. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and also heterogeneous models exhibit better results than homogeneous models for real and benchmark data sets of intrusion detection.
Long-range interacting systems in the unconstrained ensemble
Latella, Ivan; Pérez-Madrid, Agustín; Campa, Alessandro; Casetti, Lapo; Ruffo, Stefano
2017-01-01
Completely open systems can exchange heat, work, and matter with the environment. While energy, volume, and number of particles fluctuate under completely open conditions, the equilibrium states of the system, if they exist, can be specified using the temperature, pressure, and chemical potential as control parameters. The unconstrained ensemble is the statistical ensemble describing completely open systems and the replica energy is the appropriate free energy for these control parameters from which the thermodynamics must be derived. It turns out that macroscopic systems with short-range interactions cannot attain equilibrium configurations in the unconstrained ensemble, since temperature, pressure, and chemical potential cannot be taken as a set of independent variables in this case. In contrast, we show that systems with long-range interactions can reach states of thermodynamic equilibrium in the unconstrained ensemble. To illustrate this fact, we consider a modification of the Thirring model and compare the unconstrained ensemble with the canonical and grand-canonical ones: The more the ensemble is constrained by fixing the volume or number of particles, the larger the space of parameters defining the equilibrium configurations.
Three-model ensemble wind prediction in southern Italy
Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo
2016-03-01
Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.
Ensembles of a small number of conformations with relative populations
Energy Technology Data Exchange (ETDEWEB)
Vammi, Vijay, E-mail: vsvammi@iastate.edu; Song, Guang, E-mail: gsong@iastate.edu [Iowa State University, Bioinformatics and Computational Biology Program, Department of Computer Science (United States)
2015-12-15
In our previous work, we proposed a new way to represent protein native states, using ensembles of a small number of conformations with relative Populations, or ESP in short. Using Ubiquitin as an example, we showed that using a small number of conformations could greatly reduce the potential of overfitting and assigning relative populations to protein ensembles could significantly improve their quality. To demonstrate that ESP indeed is an excellent alternative to represent protein native states, in this work we compare the quality of two ESP ensembles of Ubiquitin with several well-known regular ensembles or average structure representations. Extensive amount of significant experimental data are employed to achieve a thorough assessment. Our results demonstrate that ESP ensembles, though much smaller in size comparing to regular ensembles, perform equally or even better sometimes in all four different types of experimental data used in the assessment, namely, the residual dipolar couplings, residual chemical shift anisotropy, hydrogen exchange rates, and solution scattering profiles. This work further underlines the significance of having relative populations in describing the native states.
Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.
Kelly, David; Majda, Andrew J; Tong, Xin T
2015-08-25
The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.
Long-range interacting systems in the unconstrained ensemble.
Latella, Ivan; Pérez-Madrid, Agustín; Campa, Alessandro; Casetti, Lapo; Ruffo, Stefano
2017-01-01
Completely open systems can exchange heat, work, and matter with the environment. While energy, volume, and number of particles fluctuate under completely open conditions, the equilibrium states of the system, if they exist, can be specified using the temperature, pressure, and chemical potential as control parameters. The unconstrained ensemble is the statistical ensemble describing completely open systems and the replica energy is the appropriate free energy for these control parameters from which the thermodynamics must be derived. It turns out that macroscopic systems with short-range interactions cannot attain equilibrium configurations in the unconstrained ensemble, since temperature, pressure, and chemical potential cannot be taken as a set of independent variables in this case. In contrast, we show that systems with long-range interactions can reach states of thermodynamic equilibrium in the unconstrained ensemble. To illustrate this fact, we consider a modification of the Thirring model and compare the unconstrained ensemble with the canonical and grand-canonical ones: The more the ensemble is constrained by fixing the volume or number of particles, the larger the space of parameters defining the equilibrium configurations.
Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast
Directory of Open Access Journals (Sweden)
Jinyin Ye
2016-01-01
Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.
Concrete ensemble Kalman filters with rigorous catastrophic filter divergence
Kelly, David; Majda, Andrew J.; Tong, Xin T.
2015-01-01
The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature. PMID:26261335
EnsembleGASVR: A novel ensemble method for classifying missense single nucleotide polymorphisms
Rapakoulia, Trisevgeni
2014-04-26
Motivation: Single nucleotide polymorphisms (SNPs) are considered the most frequently occurring DNA sequence variations. Several computational methods have been proposed for the classification of missense SNPs to neutral and disease associated. However, existing computational approaches fail to select relevant features by choosing them arbitrarily without sufficient documentation. Moreover, they are limited to the problem ofmissing values, imbalance between the learning datasets and most of them do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel evolutionary embedded algorithm to locate close to optimal Support Vector Regression models. In its second step, these models are combined to extract a universal predictor, which is less prone to overfitting issues, systematizes the rebalancing of the learning sets and uses an internal approach for solving the missing values problem without loss of information. Confidence scores support all the predictions and the model becomes tunable by modifying the classification thresholds. An extensive study was performed for collecting the most relevant features for the problem of classifying SNPs, and a superset of 88 features was constructed. Experimental results show that the proposed framework outperforms well-known algorithms in terms of classification performance in the examined datasets. Finally, the proposed algorithmic framework was able to uncover the significant role of certain features such as the solvent accessibility feature, and the top-scored predictions were further validated by linking them with disease phenotypes. © The Author 2014.
Directory of Open Access Journals (Sweden)
E. Crestani
2013-04-01
Full Text Available Estimating the spatial variability of hydraulic conductivity K in natural aquifers is important for predicting the transport of dissolved compounds. Especially in the nonreactive case, the plume evolution is mainly controlled by the heterogeneity of K. At the local scale, the spatial distribution of K can be inferred by combining the Lagrangian formulation of the transport with a Kalman-filter-based technique and assimilating a sequence of time-lapse concentration C measurements, which, for example, can be evaluated on site through the application of a geophysical method. The objective of this work is to compare the ensemble Kalman filter (EnKF and the ensemble smoother (ES capabilities to retrieve the hydraulic conductivity spatial distribution in a groundwater flow and transport modeling framework. The application refers to a two-dimensional synthetic aquifer in which a tracer test is simulated. Moreover, since Kalman-filter-based methods are optimal only if each of the involved variables fit to a Gaussian probability density function (pdf and since this condition may not be met by some of the flow and transport state variables, issues related to the non-Gaussianity of the variables are analyzed and different transformation of the pdfs are considered in order to evaluate their influence on the performance of the methods. The results show that the EnKF reproduces with good accuracy the hydraulic conductivity field, outperforming the ES regardless of the pdf of the concentrations.
On evaluation of ensemble precipitation forecasts with observation-based ensembles
Directory of Open Access Journals (Sweden)
S. Jaun
2007-04-01
Full Text Available Spatial interpolation of precipitation data is uncertain. How important is this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation forecasts? These questions are discussed by experimental evaluation of the COSMO consortium's limited-area ensemble prediction system COSMO-LEPS. The applied performance measure is the often used Brier skill score (BSS. The observational references in the evaluation are (a analyzed rain gauge data by ordinary Kriging and (b ensembles of interpolated rain gauge data by stochastic simulation. This permits the consideration of either a deterministic reference (the event is observed or not with 100% certainty or a probabilistic reference that makes allowance for uncertainties in spatial averaging. The evaluation experiments show that the evaluation uncertainties are substantial even for the large area (41 300 km2 of Switzerland with a mean rain gauge distance as good as 7 km: the one- to three-day precipitation forecasts have skill decreasing with forecast lead time but the one- and two-day forecast performances differ not significantly.
Input-output theory for waveguide QED with an ensemble of inhomogeneous atoms
Lalumière, Kevin; Sanders, Barry C.; van Loo, A. F.; Fedorov, A.; Wallraff, A.; Blais, A.
2013-10-01
We study the collective effects that emerge in waveguide quantum electrodynamics where several (artificial) atoms are coupled to a one-dimensional superconducting transmission line. Since single microwave photons can travel without loss for a long distance along the line, real and virtual photons emitted by one atom can be reabsorbed or scattered by a second atom. Depending on the distance between the atoms, this collective effect can lead to super- and subradiance or to a coherent exchange-type interaction between the atoms. Changing the artificial atoms transition frequencies, something which can be easily done with superconducting qubits (two levels artificial atoms), is equivalent to changing the atom-atom separation and thereby opens the possibility to study the characteristics of these collective effects. To study this waveguide quantum electrodynamics system, we extend previous work and present an effective master equation valid for an ensemble of inhomogeneous atoms driven by a coherent state. Using input-output theory, we compute analytically and numerically the elastic and inelastic scattering and show how these quantities reveal information about collective effects. These theoretical results are compatible with recent experimental results using transmon qubits coupled to a superconducting one-dimensional transmission line [van Loo (unpublished)].
Vanuytrecht, E.; Raes, D.; Willems, P.; Semenov, M.
2012-04-01
Global Circulation Models (GCMs) are sophisticated tools to study the future evolution of the climate. Yet, the coarse scale of GCMs of hundreds of kilometers raises questions about the suitability for agricultural impact assessments. These assessments are often made at field level and require consideration of interactions at sub-GCM grid scale (e.g., elevation-dependent climatic changes). Regional climate models (RCMs) were developed to provide climate projections at a spatial scale of 25-50 km for limited regions, e.g. Europe (Giorgi and Mearns, 1991). Climate projections from GCMs or RCMs are available as multi-model ensembles. These ensembles are based on large data sets of simulations produced by modelling groups worldwide, who performed a set of coordinated climate experiments in which climate models were run for a common set of experiments and various emissions scenarios (Knutti et al., 2010). The use of multi-model ensembles in climate change studies is an important step in quantifying uncertainty in impact predictions, which will underpin more informed decisions for adaptation and mitigation to changing climate (Semenov and Stratonovitch, 2010). The objective of our study was to evaluate the effect of the spatial scale of climate projections on climate change impacts for cereals in Belgium. Climate scenarios were based on two multi-model ensembles, one comprising 15 GCMs of the Coupled Model Intercomparison Project phase 3 (CMIP3; Meehl et al., 2007) with spatial resolution of 200-300 km, the other comprising 9 RCMs of the EU-ENSEMBLES project (van der Linden and Mitchell, 2009) with spatial resolution of 25 km. To be useful for agricultural impact assessments, the projections of GCMs and RCMs were downscaled to the field level. Long series (240 cropping seasons) of local-scale climate scenarios were generated by the LARS-WG weather generator (Semenov et al., 2010) via statistical inference. Crop growth and development were simulated with the Aqua
Directory of Open Access Journals (Sweden)
G. Thirel
2010-04-01
Full Text Available The use of ensemble streamflow forecasts is developing in the international flood forecasting services. Such systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM hydro-meteorological suite, which initializes the ensemble streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of Météo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF 10-day Ensemble Prediction System (EPS. Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm Rate, etc., especially
Combining 2-m temperature nowcasting and short range ensemble forecasting
Directory of Open Access Journals (Sweden)
A. Kann
2011-12-01
Full Text Available During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG since 2006 (Haiden et al., 2011, provides short range deterministic forecasts at high temporal (15 min–60 min and spatial (1 km resolution. An INCA Ensemble (INCA-EPS of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting which is running operationally at ZAMG (Wang et al., 2011. The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion for Gaussian distributed continuous
Walcott, Sam
2013-03-01
Interactions between the proteins actin and myosin drive muscle contraction. Properties of a single myosin interacting with an actin filament are largely known, but a trillion myosins work together in muscle. We are interested in how single-molecule properties relate to ensemble function. Myosin's reaction rates depend on force, so ensemble models keep track of both molecular state and force on each molecule. These models make subtle predictions, e.g. that myosin, when part of an ensemble, moves actin faster than when isolated. This acceleration arises because forces between molecules speed reaction kinetics. Experiments support this prediction and allow parameter estimates. A model based on this analysis describes experiments from single molecule to ensemble. In vivo, actin is regulated by proteins that, when present, cause the binding of one myosin to speed the binding of its neighbors; binding becomes cooperative. Although such interactions preclude the mean field approximation, a set of linear ODEs describes these ensembles under simplified experimental conditions. In these experiments cooperativity is strong, with the binding of one molecule affecting ten neighbors on either side. We progress toward a description of myosin ensembles under physiological conditions.
Super-Resolution Imaging on Microfluidic Super-Resolution Near-Field Structure
Institute of Scientific and Technical Information of China (English)
WANG Pei; TANG Lin; ZHANG Dou-Guo; LU Yong-Hua; JIAO Xiao-Jin; XIE Jian-Ping; MING Hai
2005-01-01
@@ We present a new concept of the microfluidic super-resolution near-field structure (MSRENS) based on a microfluidic structure and a super-resolution near-field structure. The near-field distance control, "nano-probe"and scanning can be realized simultaneously using the MSRENS, which is similar to a near-field scanning optical microscope. The design and simulation results are presented. Numerical simulation has demonstrated that the MSRENS with spatial resolution beyond the diffraction limit could be applicable in chemistry, biologics, and many other fields.
SuperB: An opportunity to study baryons with beauty and bottom super-nuclei
Energy Technology Data Exchange (ETDEWEB)
Feliciello, A., E-mail: Alessandro.Feliciello@to.infn.it [Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy)
2012-05-01
SuperB is an INFN flagship project for a new high-luminosity heavy-flavor factory. Along with its companion detector, it is dedicated to the search for CP violation effects in the B meson sector with the aim of looking for direct and indirect signals of new physics, beyond the Standard Model. However it could offer as well the opportunity for a systematic, high-statistics study of b baryon properties and for a search for bottom super-nuclei, that is bound nuclear systems with an explicit content of beauty.
RESEARCH NOTES On the support of super-Brownian motion with super-Brownian immigration
Institute of Scientific and Technical Information of China (English)
洪文明; 钟惠芳
2001-01-01
The support properties of the super Brownian motion with random immigration Xρ1 are considered,where the immigration rate is governed by the trajectory of another super-Brownian motion ρ. When both the initial state Xρo of the process and the immigration rate process ρo are of finite measure and with compact supports, the probability of the support of the process Xρi dominated by a ball is given by the solutions of a singular elliptic boundary value problem.
Super-hybrid composites - An emerging structural material
Chamis, C. C.; Lark, R. F.; Sullivan, T. L.
1975-01-01
Specimens of super-hybrids and advanced fiber composites were subjected to extensive tests to determine their mechanical properties, including impact and thermal fatigue. The super-hybrids were fabricated by a procedure similar to that reported by Chamis et al., (1975). Super-hybrids subjected to 1000 cycles of thermal fatigue from -100 to 300 F retained over 90% of their longitudinal flexural strength and over 75% of their transverse flexural strength; their transverse flexural strength may be as high as 8 times that of a commercially supplied boron/1100-Al composite. The thin specimen Izod longitudinal impact resistance of the super-hybrids was twice that of the boron/110-Al material. Super-hybrids subjected to transverse tensile loads exhibited nonlinear stress-strain relationships. The experimentally determined initial membrane (in-plane) and bending elastic properties of super-hybrids were predicted adequately by linear laminate analysis.
On Super Edge-Antimagicness of Subdivided Stars
Directory of Open Access Journals (Sweden)
Raheem A.
2015-11-01
Full Text Available Enomoto, Llado, Nakamigawa and Ringel (1998 defined the concept of a super (a, 0-edge-antimagic total labeling and proposed the conjecture that every tree is a super (a, 0-edge-antimagic total graph. In the support of this conjecture, the present paper deals with different results on super (a, d-edge-antimagic total labeling of subdivided stars for d ∈ {0, 1, 2, 3}.
Super-resolution optical telescopes with local light diffraction shrinkage
Changtao Wang; Dongliang Tang; Yanqin Wang; Zeyu Zhao; Jiong Wang; Mingbo Pu; Yudong Zhang; Wei Yan; Ping Gao; Xiangang Luo
2015-01-01
Suffering from giant size of objective lenses and infeasible manipulations of distant targets, telescopes could not seek helps from present super-resolution imaging, such as scanning near-field optical microscopy, perfect lens and stimulated emission depletion microscopy. In this paper, local light diffraction shrinkage associated with optical super-oscillatory phenomenon is proposed for real-time and optically restoring super-resolution imaging information in a telescope system. It is found ...
The Robotic Super-LOTIS Telescope: Results & Future Plans
Williams, G. G.; Milne, P. A.; Park, H.S.; Barthelmy, S. D.; Hartmann, D. H.; Updike, A.; Hurley, K.
2008-01-01
We provide an overview of the robotic Super-LOTIS (Livermore Optical Transient Imaging System) telescope and present results from gamma-ray burst (GRB) afterglow observations using Super-LOTIS and other Steward Observatory telescopes. The 0.6-m Super-LOTIS telescope is a fully robotic system dedicated to the measurement of prompt and early time optical emission from GRBs. The system began routine operations from its Steward Observatory site atop Kitt Peak in April 2000 and currently operates ...
Addor, Nans; Clark, Martyn P.; Mizukami, Naoki
2017-04-01
Climate change impacts on hydrological processes are typically assessed using small ensembles of hydrological models. That is, a handful of hydrological models are typically driven by a larger number of climate models. Such a setup has several limitations. Because the number of hydrological models is small, only a small proportion of the model space is sampled, likely leading to an underestimation of the uncertainties in the projections. Further, sampling is arbitrary: although hydrological models should be selected to provide a representative sample of existing models (in terms of complexity and governing hypotheses), they are instead usually selected based on legacy reasons. Furthermore, running several hydrological models currently constitutes a practical challenge because each model must be setup and calibrated individually. Finally, and probably most importantly, the differences between the projected impacts cannot be directly related to differences between hydrological models, because the models are different in almost every possible aspect. We are hence in a situation in which different hydrological models deliver different projections, but for reasons that are mostly unclear, and in which the uncertainty in the projections is probably underestimated. To overcome these limitations, we are experimenting with the flexible modeling framework FUSE (Framework for Understanding Model Errors). FUSE enables to construct conceptual models piece by piece (in a "pick and mix" approach), so it can be used to generate a large number of models that mimic existing models and/or models that differ from other models in single targeted respect (e.g. how baseflow is generated). FUSE hence allows for controlled modeling experiments, and for a more systematic and exhaustive sampling of the model space. Here we explore climate change impacts over the contiguous USA on a 12km grid using two groups of three models: the first group involves the commonly used models VIC, PRMS and HEC
Quantifying Monte Carlo uncertainty in ensemble Kalman filter
Energy Technology Data Exchange (ETDEWEB)
Thulin, Kristian; Naevdal, Geir; Skaug, Hans Julius; Aanonsen, Sigurd Ivar
2009-01-15
This report is presenting results obtained during Kristian Thulin PhD study, and is a slightly modified form of a paper submitted to SPE Journal. Kristian Thulin did most of his portion of the work while being a PhD student at CIPR, University of Bergen. The ensemble Kalman filter (EnKF) is currently considered one of the most promising methods for conditioning reservoir simulation models to production data. The EnKF is a sequential Monte Carlo method based on a low rank approximation of the system covariance matrix. The posterior probability distribution of model variables may be estimated fram the updated ensemble, but because of the low rank covariance approximation, the updated ensemble members become correlated samples from the posterior distribution. We suggest using multiple EnKF runs, each with smaller ensemble size to obtain truly independent samples from the posterior distribution. This allows a point-wise confidence interval for the posterior cumulative distribution function (CDF) to be constructed. We present a methodology for finding an optimal combination of ensemble batch size (n) and number of EnKF runs (m) while keeping the total number of ensemble members ( m x n) constant. The optimal combination of n and m is found through minimizing the integrated mean square error (MSE) for the CDFs and we choose to define an EnKF run with 10.000 ensemble members as having zero Monte Carlo error. The methodology is tested on a simplistic, synthetic 2D model, but should be applicable also to larger, more realistic models. (author). 12 refs., figs.,tabs
Bayesian Processor of Ensemble for Precipitation Forecasting: A Development Plan
Toth, Z.; Krzysztofowicz, R.
2006-05-01
The Bayesian Processor of Ensemble (BPE) is a new, theoretically-based technique for probabilistic forecasting of weather variates. It is a generalization of the Bayesian Processor of Output (BPO) developed by Krzysztofowicz and Maranzano for processing single values of multiple predictors into a posterior distribution function of a predictand. The BPE processes an ensemble of a predictand generated by multiple integrations of a numerical weather prediction (NWP) model, and optimally fuses the ensemble with climatic data in order to quantify uncertainty about the predictand. As is well known, Bayes theorem provides the optimal theoretical framework for fusing information from different sources and for obtaining the posterior distribution function of a predictand. Using a family of such distribution functions, a given raw ensemble can be mapped into a posterior ensemble, which is well calibrated, has maximum informativeness, and preserves the spatio-temporal and cross-variate dependence structure of the NWP output fields. The challenge is to develop and test the BPE suitable for operational forecasting. This talk will present the basic design components of the BPE, along with a discussion of the climatic and training data to be used in its potential application at the National Centers for Environmental Prediction (NCEP). The technique will be tested first on quasi-normally distributed variates and next on precipitation variates. For reasons of economy, the BPE will be applied on the relatively coarse resolution grid corresponding to the ensemble output, and then the posterior ensemble will be downscaled to finer grids such as that of the National Digital Forecast Database (NDFD).
Spin groups of super metrics and a theorem of Rogers
Fulp, Ronald
2017-01-01
We derive the canonical forms of super Riemannian metrics and the local isometry groups of such metrics. For certain super metrics we also compute the simply connected covering groups of the local isometry groups and interpret these as local spin groups of the super metric. Super metrics define reductions OSg of the relevant frame bundle. When principal bundles S˜g exist with structure group the simply connected covering group G ˜ of the structure group of OSg , representations of G ˜ define vector bundles associated to S˜g whose sections are "spinor fields" associated with the super metric g . Using a generalization of a Theorem of Rogers, which is itself one of the main results of this paper, we show that for super metrics we call body reducible, each such simply connected covering group G ˜ is a super Lie group with a conventional super Lie algebra as its corresponding super Lie algebra. Some of our results were known to DeWitt (1984) using formal Grassmann series and others were known by Rogers using finitely many Grassmann generators and passing to a direct limit. We work exclusively in the category of G∞ supermanifolds with G∞ mappings. Our supernumbers are infinite series of products of Grassmann generators subject to convergence in the ℓ1 norm introduced by Rogers (1980, 2007).
New Results from Super-K and K2K
Wilkes, R J
2002-01-01
This paper summarizes recent (as of SSI-02, in some cases updated in November, 2002) results from the Super-Kamiokande and K2K experiments. The interpretation of Super-Kamiokande results on atmospheric and solar neutrinos provides strong evidence for neutrino oscillations, hence non-zero neutrino mass. While statistics are still limited, K2K data are consistent with Super-Kamiokande results on neutrino oscillations. The effort to reconstruct Super-Kamiokande following a cascade of phototube implosions in November, 2001 is described. Plans for the future are also discussed.
Video super-resolution using simultaneous motion and intensity calculations
DEFF Research Database (Denmark)
Keller, Sune Høgild; Lauze, Francois Bernard; Nielsen, Mads
2011-01-01
for the joint estimation of a super-resolution sequence and its flow field. Via the calculus of variations, this leads to a coupled system of partial differential equations for image sequence and motion estimation. We solve a simplified form of this system and as a by-product we indeed provide a motion field...... for super-resolved sequences. Computing super-resolved flows has to our knowledge not been done before. Most advanced super-resolution (SR) methods found in literature cannot be applied to general video with arbitrary scene content and/or arbitrary optical flows, as it is possible with our simultaneous VSR...
Directory of Open Access Journals (Sweden)
Fucai You
2014-01-01
Full Text Available A six-component super-Ablowitz-Kaup-Newell-Segur (-AKNS hierarchy is proposed by the zero curvature equation associated with Lie superalgebras. Supertrace identity is used to furnish the super-Hamiltonian structures for the resulting nonlinear superintegrable hierarchy. Furthermore, we derive the infinite conservation laws of the first two nonlinear super-AKNS equations in the hierarchy by utilizing spectral parameter expansions. PACS: 02.30.Ik; 02.30.Jr; 02.20.Sv.
Directory of Open Access Journals (Sweden)
E. Crestani
2012-11-01
Full Text Available The significance of estimating the spatial variability of the hydraulic conductivity K in natural aquifers is relevant to the possibility of defining the space and time evolution of a non-reactive plume, since the transport of a solute is mainly controlled by the heterogeneity of K. At the local scale, the spatial distribution of K can be inferred by combining the Lagrangian formulation of the transport with a Kalman filter-based technique and assimilating a sequence of time-lapse concentration C measurements, which, for example, can be evaluated on-site through the application of a geophysical method. The objective of this work is to compare the ensemble Kalman filter (EnKF and the ensemble smoother (ES capabilities to retrieve the hydraulic conductivity spatial distribution in a groundwater flow and transport modeling framework. The application refers to a two-dimensional synthetic aquifer in which a tracer test is simulated. Moreover, since Kalman filter-based methods are optimal only if each of the involved variables fit to a Gaussian probability density function (pdf and since this condition may not be met by some of the flow and transport state variables, issues related to the non-Gaussianity of the variables are analyzed and different transformation of the pdfs are considered in order to evaluate their influence on the performance of the methods. The results show that the EnKF reproduces with good accuracy the hydraulic conductivity field, outperforming the ES regardless of the pdf of the concentrations.
Precipitation and temperature ensemble forecasts from single-value forecasts
Directory of Open Access Journals (Sweden)
J. Schaake
2007-04-01
Full Text Available A procedure is presented to construct ensemble forecasts from single-value forecasts of precipitation and temperature. This involves dividing the spatial forecast domain and total forecast period into a number of parts that are treated as separate forecast events. The spatial domain is divided into hydrologic sub-basins. The total forecast period is divided into time periods, one for each model time step. For each event archived values of forecasts and corresponding observations are used to model the joint distribution of forecasts and observations. The conditional distribution of observations for a given single-value forecast is used to represent the corresponding probability distribution of events that may occur for that forecast. This conditional forecast distribution subsequently is used to create ensemble members that vary in space and time using the "Schaake Shuffle" (Clark et al, 2004. The resulting ensemble members have the same space-time patterns as historical observations so that space-time joint relationships between events that have a significant effect on hydrological response tend to be preserved.
Forecast uncertainty is space and time-scale dependent. For a given lead time to the beginning of the valid period of an event, forecast uncertainty depends on the length of the forecast valid time period and the spatial area to which the forecast applies. Although the "Schaake Shuffle" procedure, when applied to construct ensemble members from a time-series of single value forecasts, may preserve some of this scale dependency, it may not be sufficient without additional constraint. To account more fully for the time-dependent structure of forecast uncertainty, events for additional "aggregate" forecast periods are defined as accumulations of different "base" forecast periods.
The generated ensemble members can be ingested by an Ensemble Streamflow Prediction system to produce ensemble forecasts of streamflow and other
Seamless Hourly Rainfall Ensemble Forecasts for 0 - 10 days
Cooper, Shaun; Seed, Alan
2014-05-01
The Australian Bureau of Meteorology uses a number of Numerical Weather Prediction (NWP) models to generate deterministic rainfall forecasts over a range of lead-times, each with a different resolution in space and time and with different forecast domains. High resolution regional NWP models are used to generate forecasts for the first three days, and are typically more accurate than lower resolution Global NWP models that produce forecasts for longer lead times. Consequently, there is a requirement for a seamless forecast system that is able to blend the various NWP forecasts into a single forecast with a uniform resolution over the entire forecast period. NWP rainfall forecasts contain errors at scales that are significant for even large river basins, and ensemble hydrological prediction systems require ensembles of the order of 100 members, which is well beyond the size that can be generated by NWP ensemble systems. The idea, therefore, is to blend the NWP models in such a way that recognises the skill of the NWP at a particular scale and lead time and to use a stochastic model of forecast errors to perturb the blended deterministic forecast to generate a large ensemble. NWP uncertainties are scale and forecast lead time dependent, especially at long forecast lead times, and are characteristic to each model. By blending the models scale by scale it is possible to recognise the increased skill of the models at larger spatial scales and shorter lead times. The stochastic model is applied at each scale, adding increasingly more variability at smaller spatial scales, while preserving the space-time structure of rain. This process allows an ensemble to be generated by blending deterministic forecasts. Two NWP models from the Bureau, ACCESS-G (Global) (~40 km by ~40 km, 3 hourly out to 10 days) and ACCESS-R (Regional) (~12 km by ~12 km, 1 hourly out to 3 days), are downscaled and blended with the stochastic model to produce an ensemble of hourly forecasts out to 10
Hierarchical Bayes Ensemble Kalman Filter for geophysical data assimilation
Tsyrulnikov, Michael; Rakitko, Alexander
2016-04-01
In the Ensemble Kalman Filter (EnKF), the forecast error covariance matrix B is estimated from a sample (ensemble), which inevitably implies a degree of uncertainty. This uncertainty is especially large in high dimensions, where the affordable ensemble size is orders of magnitude less than the dimensionality of the system. Common remedies include ad-hoc devices like variance inflation and covariance localization. The goal of this study is to optimize the account for the inherent uncertainty of the B matrix in EnKF. Following the idea by Myrseth and Omre (2010), we explicitly admit that the B matrix is unknown and random and estimate it along with the state (x) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components P and Q of the B matrix into the extended control vector (x,P,Q). Similarly, we break the traditional forecast ensemble into the predictability-error related ensemble and model-error related ensemble. The reason for the separation of model errors from predictability errors is the fundamental difference between the two sources of error. Model error are external (i.e. do not depend on the filter's performance) whereas predictability errors are internal to a filter (i.e. are determined by the filter's behavior). At the analysis step, we specify Inverse Wishart based priors for the random matrices P and Q and conditionally Gaussian prior for the state x. Then, we update the prior distribution of (x,P,Q) using both observation and ensemble data, so that ensemble members are used as generalized observations and ordinary observations are allowed to influence the covariances. We show that for linear dynamics and linear observation operators, conditional Gaussianity of the state is preserved in the course of filtering. At the forecast
Trends in the predictive performance of raw ensemble weather forecasts
Hemri, Stephan; Scheuerer, Michael; Pappenberger, Florian; Bogner, Konrad; Haiden, Thomas
2015-04-01
Over the last two decades the paradigm in weather forecasting has shifted from being deterministic to probabilistic. Accordingly, numerical weather prediction (NWP) models have been run increasingly as ensemble forecasting systems. The goal of such ensemble forecasts is to approximate the forecast probability distribution by a finite sample of scenarios. Global ensemble forecast systems, like the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, are prone to probabilistic biases, and are therefore not reliable. They particularly tend to be underdispersive for surface weather parameters. Hence, statistical post-processing is required in order to obtain reliable and sharp forecasts. In this study we apply statistical post-processing to ensemble forecasts of near-surface temperature, 24-hour precipitation totals, and near-surface wind speed from the global ECMWF model. Our main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the post-processed forecasts. The ECMWF ensemble is under continuous development, and hence its forecast skill improves over time. Parts of these improvements may be due to a reduction of probabilistic bias. Thus, we first hypothesize that the gain by post-processing decreases over time. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations we generate post-processed forecasts by ensemble model output statistics (EMOS) for each station and variable. Parameter estimates are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over rolling training periods that consist of the n days preceding the initialization dates. Given the higher average skill in terms of CRPS of the post-processed forecasts for all three variables, we analyze the evolution of the difference in skill between raw ensemble and EMOS forecasts. The fact that the gap in skill remains almost constant over time, especially for near
Super-Liouville - Double Liouville correspondence
Hadasz, Leszek
2014-01-01
The AGT motivated relation between the tensor product of the N=1 super-Liouville field theory with the imaginary free fermion (SL) and a certain projected tensor products of the real and the imaginary Liouville field theories (LL) is analyzed. Using conformal field theory techniques we give a complete proof of the equivalence in the NS sector. It is shown that SL-LL correspondence is based on the equivalence of chiral objects including suitably chosen chiral structure constants of all three Liouville theories involved.
2008-06-01
Today, at an international conference, a team of European astronomers announced a remarkable breakthrough in the field of extra-solar planets. Using the HARPS instrument at the ESO La Silla Observatory, they have found a triple system of super-Earths around the star HD 40307. Moreover, looking at their entire sample studied with HARPS, the astronomers count a total of 45 candidate planets with a mass below 30 Earth masses and an orbital period shorter than 50 days. This implies that one solar-like star out of three harbours such planets. A trio of Super-Earths ESO PR Photo 19a/08 A trio of Super-Earths "Does every single star harbour planets and, if yes, how many?" wonders planet hunter Michel Mayor from Geneva Observatory. "We may not yet know the answer but we are making huge progress towards it." Since the discovery in 1995 of a planet around the star 51 Pegasi by Mayor and Didier Queloz, more than 270 exoplanets have been found, mostly around solar-like stars. Most of these planets are giants, such as Jupiter or Saturn, and current statistics show that about 1 out of 14 stars harbours this kind of planet. "With the advent of much more precise instruments such as the HARPS spectrograph on ESO's 3.6-m telescope at La Silla, we can now discover smaller planets, with masses between 2 and 10 times the Earth's mass," says Stéphane Udry, one of Mayor's colleagues. Such planets are called super-Earths, as they are more massive than the Earth but less massive than Uranus and Neptune (about 15 Earth masses). The group of astronomers have now discovered a system of three super-Earths around a rather normal star, which is slightly less massive than our Sun, and is located 42 light-years away towards the southern Doradus and Pictor constellations. "We have made very precise measurements of the velocity of the star HD 40307 over the last five years, which clearly reveal the presence of three planets," says Mayor. The planets, having 4.2, 6.7, and 9.4 times the mass of the
Energy Technology Data Exchange (ETDEWEB)
Demmel, James W.; Gilbert, John R.; Li, Xiaoye S.
1999-11-01
This document describes a collection of three related ANSI C subroutine libraries for solving sparse linear systems of equations AX = B: Here A is a square, nonsingular, n x n sparse matrix, and X and B are dense n x nrhs matrices, where nrhs is the number of right-hand sides and solution vectors. Matrix A need not be symmetric or definite; indeed, SuperLU is particularly appropriate for matrices with very unsymmetric structure. All three libraries use variations of Gaussian elimination optimized to take advantage both of sparsity and the computer architecture, in particular memory hierarchies (caches) and parallelism.
Production of super-smooth articles
Energy Technology Data Exchange (ETDEWEB)
Duchane, D.V.
1981-05-29
Super-smooth rounded or formed articles made of thermoplastic materials including various poly(methyl methacrylate) or acrylonitrile-butadiene-styrene copolymers are produced by immersing the articles into a bath, the composition of which is slowly changed with time. The starting composition of the bath is made up of at least one solvent for the polymer and a diluent made up of at least one nonsolvent for the polymer and optional materials which are soluble in the bath. The resulting extremely smooth articles are useful as mandrels for laser fusion and should be useful for a wide variety of other purposes, for example lenses.
Emergent Super-Virasoro on Magnetic Branes
D'Hoker, Eric
2016-01-01
The low energy limit of the stress tensor, gauge current, and supercurrent two-point correlators are calculated in the background of the supersymmetric magnetic brane solution to gauged five-dimensional supergravity constructed by Almuhairi and Polchinski. The resulting correlators provide evidence for the emergence of an N=2 super-Virasoro algebra of right-movers, in addition to a bosonic Virasoro algebra and a $U(1) \\oplus U(1)$-current algebra of left-movers (or the parity transform of left- and right-movers depending on the sign of the magnetic field), in the holographically dual strongly interacting two-dimensional effective field theory of the lowest Landau level.
Super-utilizers get red carpet treatment.
2014-01-01
MetroHealth Medical Center in Cleveland has partnered with two health plans to provide intensive care coordination for high-cost patients with multiple medical problems and, often, behavioral health issues. Nurse practitioners at two primary care sites provide one-on-one care coordination for super-utilizers. They assess the patients' needs, help coordinate community resources, and prepare a treatment plan that is flagged when patients visit the emergency department. The nurse practitioners meet with health plan representatives monthly and brainstorm on ways to meet patients' needs.
The Super-B Project Accelerator Status
Energy Technology Data Exchange (ETDEWEB)
Biagini, M.E.; Alesini, D.; Boni, R.; Boscolo, M.; Demma, T.; Drago, A.; Esposito, M.; Guiducci, S.; Marcellini, F.; Mazzitelli, G.; Preger, M.; Raimondi, P.; Sanelli, C.; Serio, M.; Stecchi, A.; Stella, A.; Tomassini, S.; Zobov, M.; /Frascati; Bertsche, K.; Brachmann, A.; Cai, Y.; /SLAC /Novosibirsk, IYF /Annecy, LAPP /LPSC, Grenoble /Orsay, LAL /Saclay /Pisa U. /CERN
2011-08-17
The SuperB project is an international effort aiming at building in Italy a very high luminosity e{sup +}e{sup -} (10{sup 36} cm{sup -2} sec{sup -1}) asymmetric collider at the Y(4S) energy in the CM. The accelerator design has been extensively studied and changed during the past year. The present design, based on the new collision scheme, with large Piwinski angle and the use of 'crab waist' sextupoles already successfully tested at the DA{Phi}NE {Phi}-Factory at LNF Frascati, provides larger flexibility, better dynamic aperture and spin manipulation sections in the Low Energy Ring (LER) for longitudinal polarization of the electron beam at the Interaction Point (IP). The Interaction Region (IR) has been further optimized in terms of apertures and reduced backgrounds in the detector. The injector complex design has been also updated. A summary of the project status will be presented in this paper. The SuperB collider can reach a peak luminosity of 10{sup 36} cm{sup -2} sec{sup -1} with beam currents and bunch lengths similar to those of the past and present e{sup +}e{sup -} Factories, through the use of smaller emittances and new scheme of crossing angle collision. The beams are stored in two rings at 6.7 GeV (HER) and 4.2 GeV (LER). Unique features of the project are the polarization of the electron beam in the LER and the possibility to decrease the energies for running at the {tau}/charm threshold. The option to reuse the PEP-II B-Factory (SLAC) hardware will allow reducing costs. The SuperB facility will require a big complex of civil infrastructure. The main construction, which will house the final part of the LINAC, the injection lines, the damping rings, and the storage rings, will be mainly underground. Two sites have been considered: the campus of Tor Vergata University near Frascati, and the INFN Frascati Laboratory. No decision has been made yet. A footprint of the possible SuperB layout on the LNF area is shown in Fig. 1.
Super computer made with Linux cluster
Energy Technology Data Exchange (ETDEWEB)
Lee, Jeong Hun; Oh, Yeong Eun; Kim, Jeong Seok
2002-01-15
This book consists of twelve chapters, which introduce super computer made with Linux cluster. The contents of this book are Linux cluster, the principle of cluster, design of Linux cluster, general things for Linux, building up terminal server and client, Bear wolf cluster by Debian GNU/Linux, cluster system with red hat, Monitoring system, application programming-MPI, on set-up and install application programming-PVM, with PVM programming and XPVM application programming-open PBS with composition and install and set-up and GRID with GRID system, GSI, GRAM, MDS, its install and using of tool kit.
Transfer function characteristics of super resolving systems
Milster, Tom D.; Curtis, Craig H.
1992-01-01
Signal quality in an optical storage device greatly depends on the optical system transfer function used to write and read data patterns. The problem is similar to analysis of scanning optical microscopes. Hopkins and Braat have analyzed write-once-read-many (WORM) optical data storage devices. Herein, transfer function analysis of magnetooptic (MO) data storage devices is discussed with respect to improving transfer-function characteristics. Several authors have described improving the transfer function as super resolution. However, none have thoroughly analyzed the MO optical system and effects of the medium. Both the optical system transfer function and effects of the medium of this development are discussed.
Medical care at the Super Bowl.
Ellis, J M
2000-06-01
Although coordinating medical care at the Super Bowl is something that we look forward to and have a lot of fun doing, we take it very seriously and understand the importance of delivering medical care at what many people consider to be the greatest sporting event in the world. It is certainly one of the most watched and recognized events in the world and because of this, we attempt to set up a system that will allow for the best medical care available and standardization of this medical care through our experience within Medical Sports Group.
Ensemble size impact on the decadal predictive skill assessment
Directory of Open Access Journals (Sweden)
Frank Sienz
2016-12-01
Full Text Available Retrospective prediction experiments have to be performed to estimate the skill of decadal prediction systems. These are necessarily restricted in the number due to the computational constraints. From weather and seasonal prediction it is known that the ensemble size is crucial to yield reliable predictions. Differences are expected for decadal predictions due to the differing time-scales of the involved processes and the longer prediction horizon. A conceptual model is applied that enables the systematic analysis of ensemble size dependencies in a framework close to that of decadal predictions. Differences are quantified in terms of the confidence intervals coverage and the power of statistical tests for prediction scores. In addition, the concepts are applied to decadal predicitions of the MiKlip Baseline1 system. It is shown that small ensemble, as well as hindcast sample sizes lead to biased test performances in a way that the detection of a present prediction skill is hampered. Experiments with ensemble sizes smaller than 10 are not recommended to evaluate decadal prediction skill or as basis for the prediction system developement. For regions with low signal-to-noise ratios much larger ensembles are required and it is shown that in this case successful decadal predictions are possible for the Central European summer temperatures.
Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach
Energy Technology Data Exchange (ETDEWEB)
Chertkov, Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Skolkovo Inst. of Science and Technology, Moscow (Russia); Chernyak, Vladimir [Wayne State Univ., Detroit, MI (United States). Dept. of Chemistry
2017-01-17
Thermostatically Controlled Loads (TCL), e.g. air-conditioners and heaters, are by far the most wide-spread consumers of electricity. Normally the devices are calibrated to provide the so-called bang-bang control of temperature - changing from on to off , and vice versa, depending on temperature. Aggregation of a large group of similar devices into a statistical ensemble is considered, where the devices operate following the same dynamics subject to stochastic perturbations and randomized, Poisson on/off switching policy. We analyze, using theoretical and computational tools of statistical physics, how the ensemble relaxes to a stationary distribution and establish relation between the re- laxation and statistics of the probability flux, associated with devices' cycling in the mixed (discrete, switch on/off , and continuous, temperature) phase space. This allowed us to derive and analyze spec- trum of the non-equilibrium (detailed balance broken) statistical system. and uncover how switching policy affects oscillatory trend and speed of the relaxation. Relaxation of the ensemble is of a practical interest because it describes how the ensemble recovers from significant perturbations, e.g. forceful temporary switching o aimed at utilizing flexibility of the ensemble in providing "demand response" services relieving consumption temporarily to balance larger power grid. We discuss how the statistical analysis can guide further development of the emerging demand response technology.
Are paleoclimate model ensembles consistent with the MARGO data synthesis?
Directory of Open Access Journals (Sweden)
J. C. Hargreaves
2011-03-01
Full Text Available We investigate the consistency of various ensembles of model simulations with the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface (MARGO sea surface temperature data synthesis. We discover that while two multi-model ensembles, created through the Paleoclimate Model Intercomparison Projects (PMIP and PMIP2, pass our simple tests of reliability, an ensemble based on parameter variation in a single model does not perform so well. We show that accounting for observational uncertainty in the MARGO database is of prime importance for correctly evaluating the ensembles. Perhaps surprisingly, the inclusion of a coupled dynamical ocean (compared to the use of a slab ocean does not appear to cause a wider spread in the sea surface temperature anomalies, but rather causes systematic changes with more heat transported north in the Atlantic. There is weak evidence that the sea surface temperature data may be more consistent with meridional overturning in the North Atlantic being similar for the LGM and the present day, however, the small size of the PMIP2 ensemble prevents any statistically significant results from being obtained.