UK PubMed Central (United Kingdom)

Quantum computing is a quickly growing research field. This article introduces the basic concepts of quantum computing, recent developments in quantum searching, and decoherence in a possible quantum...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

No abstract prepared.

Energy Technology Data Exchange (ETDEWEB)

Quantum computers hold the promise of solving certain computational tasks much more efficiently than classical computers. We review recent experimental advances towards a quantum computer with trapped ions. In particular, various implementations of qubits, quantum gates and some key experiments are discussed. Furthermore, we review some implementations of quantum algorithms such as a deterministic teleportation of quantum information and an error correction scheme.

Energy Technology Data Exchange (ETDEWEB)

This thesis investigates the application of artificial neural networks for the compression of image data. An algorithm is developed using the competitive learning paradigm which takes advantage of the parallel processing and classification capability of neural networks to produce an efficient implementation of vector quantization. Multi-Stage, tree searched, and classification vector quantization codebook design are adapted to the neural network design to reduce the computational cost and hardware requirements. The results show that the new algorithm provides a substantial reduction in computational costs and an improvement in performance.

CERN Document Server

Computing Networks (CNs) are defined. These are used to generalize neural and swarm architectures, namely artificial neural networks, ant colony optimization, and particle swarm optimization. The description of these architectures as CNs allows their comparison, distinguishing which properties enable them to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales.

Science.gov (United States)

During the entire performance period, from 12 May 2003 through 31 December 2006, we have conducted theoretical and computational research on quantum control problems central to quantum computation. In particular we completed a thorough and rigorous analys...

Energy Technology Data Exchange (ETDEWEB)

We survey results in lattice quantum chromodynamics from groups in the USQCD Collaboration. The main focus is on physics, but many aspects of the discussion are aimed at an audience of computational physicists.

Energy Technology Data Exchange (ETDEWEB)

A new model for computations is considered which combines the quantum computer with the chaotic dynamics amplifier, based on the logistic map. We discuss the satisfiability problem and argue that the problem can, in principle, be solved in polynomial time if one uses the new model for computations.

Science.gov (United States)

This is the homepage of "an Australian multi-university collaboration undertaking research on the fundamental physics and technology of building, at the atomic level, a solid state quantum computer in silicon together with other high potential implementations." Although attempts to develop a quantum computer have met with limited success, the centre has substantial resources invested in advancing toward practical uses of quantum computing technology. The site provides a very good introduction to the principles and implications of quantum computing, as well as details about various research projects underway at the Australian universities. Links to conference and journal papers produced by members of the centre, many from 2003, are also provided.

Energy Technology Data Exchange (ETDEWEB)

A quantum computer would put the latest PC to shame. Not only would such a device be faster than a conventional computer, but by exploiting the quantum-mechanical principle of superposition it could change the way we think about information processing. However, two key goals need to be met before a quantum computer becomes reality. The first is to be able to control the state of a single quantum bit (or 'qubit') and the second is to build a two-qubit gate that can produce 'entanglement' between the qubit states. (U.K.)

Energy Technology Data Exchange (ETDEWEB)

This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological systems, using a ...

Energy Technology Data Exchange (ETDEWEB)

Science and technology could be revolutionized by quantum computers, but building them from solid-state devices will not be easy. Robert W Keyes of IBM's research division outlines the challenges in scaling up the technology from lab experiments to practical devices. (U.K.)

International Nuclear Information System (INIS)

We study a quantum computing system using microwave photons in transmission line resonators on a superconducting chip as qubits. We show that linear optics and other controls necessary for quantum computing can be implemented by coupling to Josephson devices on the same chip. By taking advantage of the strong nonlinearities in Josephson junctions, photonic qubit interactions can be realized. We analyze the gate error rate to demonstrate that our scheme is realistic even for Josephson devices with limited decoherence times. As a conceptually innovative solution based on existing technologies, our scheme provides an integrated and scalable approach to the next key milestone for photonic qubit quantum computing.

Energy Technology Data Exchange (ETDEWEB)

This paper reports progress in the fabrication and characterization of an array of 1nm-scale colloidal particles (i.e., quantum-dot array) that can be operated to execute nontrivial and innovative computations, possibly including quantum logic. We discuss the actual fabrication of 2-nm metal clusters as an example of possible quantum dot implementation. Innovative and unconventional paradigms underlie the different stages of this work. For example, regular array geometry is achieved by directing appropriately derivatized metal clusters to preselected locations along a stretched strand of an engineered DNA sequence.

Energy Technology Data Exchange (ETDEWEB)

In this talk, we explore the feasibility of quantum computation using continuous-variable systems by means of local measurements only. In the first part of the talk, we will identify crucial limitations that arise when starting from Gaussian cluster states. This is done by resorting to a Gaussian projected entangled pair picture as well as to notions of continuous-variable quantum repeater networks. In the second part, we look at instances in which these limitations can be overcome, and how suitable encodings of qubits in oscillators and feasible non-Gaussian resource states give rise to universal schemes for quantum computing.

Energy Technology Data Exchange (ETDEWEB)

This paper presents the application of artificial neural networks to adiabatic flame temperature prediction of hydrocarbon fuels. The investigation was conducted over a wide range of operating conditions in terms of fuel composition, pressure and temperature of reactants, fuel-air equivalence ratio and fuel vapour fraction. Several neural network models for predicting the flame temperature for different applicable fuel ranges were built and examined. The proper preparation of network training data and the appropriate choice of network parameters for achieving better prediction accuracy are discussed. The neural network prediction results were compared with those calculated by a thermodynamic and chemical equilibrium-based computer code - the NASA program CET89. It was shown that trained neural network models can provide the adiabatic flame temperature prediction with a good level of ...

UK PubMed Central (United Kingdom)

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

We discuss strictly efficient models for measurement-based quantum computing using physical continuous variables, such as field modes of light. Such measurement-based quantum computing (MBQC) provides a promising paradigm for quantum computation as it does not require performing unitary gates during the computation, but rather appropriate readout. Here, we introduce novel schemes for which the resource state can be reasonably and efficiently prepared, and which notably do not require having infinite squeezing or mean energy available. What is more, error correction techniques are implementable, as the logical information is stored in finite-dimensional objects grasping correlations of the quantum states. Using the ideas of computational tensor networks we discuss how to sequentially prepare suitable ...

Energy Technology Data Exchange (ETDEWEB)

Trapped ions are a near ideal system to study quantum information processing due to the high degree of control over the ion's external confinement and internal degrees of freedom. We demonstrate the key steps necessary for trapped ion quantum computing and focus on phonon-mediated entangling gates. We highlight several key algorithms implemented over the last decade with these gates and give a detailed description of Grover's quantum database search implemented with two trapped ion qubits.

International Nuclear Information System (INIS)

We propose two schemes for the implementation of quantum discrete Fourier transform in the ion trap system. In each scheme we design a tunable two-qubit phase gate as the main ingredient. The experimental implementation of the schemes would be an important step toward complex quantum computation in the ion trap system.

International Nuclear Information System (INIS)

Atomic ensembles, comprising clouds of atoms addressed by laser fields, provide an attractive system for both the storage of quantum information and the coherent conversion of quantum information between atomic and optical degrees of freedom. We describe a scheme for full-scale quantum computing with atomic ensembles, in which qubits are encoded in symmetric collective excitations of many atoms. We consider the most important sources of error-imperfect exciton-photon coupling and photon losses-and demonstrate that the scheme is extremely robust against these processes: the required photon emission and collection efficiency threshold is #approx#>86%. Our scheme uses similar methods to those already demonstrated experimentally in the context of quantum repeater schemes and yet has information processing capabilities far beyond those proposals.

Energy Technology Data Exchange (ETDEWEB)

A novel way to extract relevant parameters associated with the outgoing ions from nuclear reactions, obtained by digitizing the signals provided by a Bragg curve spectrometer (BCS) is presented. This allowed the implementation of a more thorough pulse-shape analysis. Due to the complexity of this task, it was required to take advantage of new and more powerful computational paradigms. This was fulfilled using a back-propagation artificial neural network (ANN) as a pattern identifier. Over training of ANNs is a common problem during the training stage. In the performance of the ANN there is a compromise between its size and the size of the training set. Here, this effect will be illustrated in relation to the problem of Bragg Curve (BC) identification. (Author)

Energy Technology Data Exchange (ETDEWEB)

Linear-optical passive (LOP) devices and photon counters are sufficient to implement universal quantum computation with single photons, and particular schemes have already been proposed. In this paper we discuss the link between the algebraic structure of LOP transformations and quantum computing. We first show how to decompose the Fock space of N optical modes in finite-dimensional subspaces that are suitable for encoding strings of qubits and invariant under LOP transformations (these subspaces are related to the spaces of irreducible unitary representations of U (N). Next we show how to design in algorithmic fashion LOP circuits which implement any quantum circuit deterministically. We also present some simple examples, such as the circuits implementing a cNOT gate and a Bell state generator/analyser.

Energy Technology Data Exchange (ETDEWEB)

We introduce a novel scheme for one-way quantum computing (QC) based on the use of information encoded qubits in an effective cluster state resource. With the correct encoding structure, we show that it is possible to protect the entangled resource from phase damping decoherence, where the effective cluster state can be described as residing in a decoherence-free subspace (DFS) of its supporting quantum system. One-way QC then requires either single or two-qubit adaptive measurements. As an example where this proposal can be realized, we describe an optical lattice set-up where the scheme provides robust quantum information processing. We also outline how one can adapt the model to provide protection from other types of decoherence.

CERN Document Server

Methods and Procedures for the Verification and Validation of Artificial Neural Networks

Energy Technology Data Exchange (ETDEWEB)

We prove that the 1984 protocol of Bennett and Brassard (BB84) for quantum key distribution is secure. We first give a key distribution protocol based on entanglement purification, which can be proven secure using methods from Lo and Chau's proof of security for a similar protocol. We then show that the security of this protocol implies the security of BB84. The entanglement purification based protocol uses Calderbank-Shor-Steane codes, and properties of these codes are used to remove the use of quantum computation from the Lo-Chau protocol. (c) 2000 The American Physical Society.

International Nuclear Information System (INIS)

Methods of algebraic quantum field theory are used to classify all field- and observable algebras, whose common germ is the U(1)-current algebra. An elementary way is described to compute characters of such algebras. It exploits the Kubo-Martin-Schwinger condition for Gibbs states. (orig.).

Energy Technology Data Exchange (ETDEWEB)

A novel non-invasive approach to the on-line identification of BWR two-phase flow regimes is investigated. The proposed approach receives neutron radiography images of coolant flow recordings as its input and performs feature extraction on each image via simple and directly computable statistical operators. The extracted features are subsequently used as inputs to an ensemble of self-organizing maps whose outputs demonstrate swift and accurate classification of each image into its corresponding flow regime. The novelty of the approach lies in the use of the self-organizing map which generates the different classes by itself, according to feature similarity of the corresponding images; this contrasts traditional artificial neural networks where the user has to define both the number of distinct classes as well as to supply separate training vectors for each class.

Energy Technology Data Exchange (ETDEWEB)

Strains in multivalley semiconductors can destroy the strict equivalence of the valleys that is demanded by cubic symmetry. Significant changes in the properties of a semiconductor may result. A proposed implementation of quantum computing with donor atoms in silicon would suffer from alterations of the donor wave functions caused by strains that are produced by fabrication processes. Deliberately straining the silicon to an extent that removed all but one valley from participation in the lowest donor state, would prevent further changes in the wave function by strain. The strain required can be achieved with established technology for depositing silicon on SiGe alloys. (author)

Energy Technology Data Exchange (ETDEWEB)

Since information has been regarded os a physical entity, the field of quantum information theory has blossomed. This brings novel applications, such as quantum computation. This field has attracted the attention of numerous researchers with backgrounds ranging from computer science, mathematics and engineering, to the physical sciences. Thus, we now have an interdisciplinary field where great efforts are being made in order to build devices that should allow for the processing of information at a quantum level, and also in the understanding of the complex structure of some physical processes at a more basic level. This thesis is devoted to the theoretical study of structures at the nanometer-scale, 'nanostructures', through physical processes that mainly involve the solid-state and quantum optics, in order to propose reliable schemes for the ...

CERN Document Server

A prescription is given for computing anomalous dimensions of single trace operators in SYM at strong coupling and large $N$ using a reduced model of matrix quantum mechanics. The method involves treating some parts of the operators as "BPS condensates" which, in certain limit, have a dual description as null geodesics on the $S^5$. In the gauge theory, the condensate is similar to a representative of the chiral ring and it is described by a background of commuting matrices. Excitations around these condensates correspond to excitations around this background and take the form of ``string bits" which are dual to the "giant magnons" of Hofman and Maldacena. In fact, the matrix model approach gives a {\\it quantum} description of these string configurations and explains why the infinite momentum limit suppresses the quantum effects. This method allows, not only to derive part of the classical sigma model ...

Energy Technology Data Exchange (ETDEWEB)

We apply a notion of static renormalization to the preparation of cluster states for quantum computing, exploiting ideas from percolation theory. Such a strategy yields a novel way to cope with the randomness of non-deterministic quantum gates. This is most relevant in the context of linear optical architectures, where probabilistic gates are inevitable. We demonstrate how to efficiently construct cluster states without the need for rerouting, thereby avoiding a massive amount of feed-forward and conditional dynamics, and furthermore show that except for a single layer of fusion measurements during the preparation, all further measurements can be shifted to the final adapted single qubit measurements. Remarkably, the cluster state preparation is achieved using essentially the same scaling in resources as if deterministic gates were available. Further, techniques to reduce the size of the required resource states will be ...

Energy Technology Data Exchange (ETDEWEB)

A computational environment, as a set of MapleV R.3 routines for doing symbolic calculations in Quantum Field Theory, is presented. The Q F T package`s routines extend the standard MapleV computational domain by introducing representations for anti commutative and noncommutative objects, tensors, spinors and gauge fields, as well as related objects and procedures (Dirac matrices, differential operators, functional differentiation w.r.t indexed fields, sum rule for repeated indices, etc.). Furthermore, the Q F T routines permit the user-definition of algebra rules for the commutation/ anti commutation of operators, to be taken into account during the calculations. (author) 2 refs.

Science.gov (United States)

... Accession Number : ADA111683. Title : Coherency Effects on Retinal Neural Processes (ERG) of Pseudemys. Descriptive ...

Energy Technology Data Exchange (ETDEWEB)

The topic of supervised learning within the conceptual framework of artificial neural network (ANN) models is addressed. An ANN is a parallel distributed processing system that consists of many computationally simple processing elements interconnected through uni-directional weighted connections. Such networks, which are roughly patterned after biological nervous systems, have been proposed for use in areas in which the traditional von Neumann computer architecture has been relatively unsuccessful. Learning in these networks is accomplished through the use of algorithms that adjust the values of the connection weights. The work presented here addresses the issue of improving the rate at which ANNs can learn to achieve the mapping of an input pattern to a desired output pattern. The most successful learning algorithms for accomplishing this task are based on gradient descent error minimization techniques. However, the large ...

DEFF Research Database (Denmark)

We propose to encode a register of quantum bits in different collective electron spin wave excitations in a solid medium. Coupling to spins is enabled by locating them in the vicinity of a superconducting transmission line cavity, and making use of their strong collective coupling to the quantized radiation field. The transformation between different spin waves is achieved by applying gradient magnetic fields across the sample, while a Cooper pair box, resonant with the cavity field, may be used to carry out one- and two-qubit gate operations.

CERN Document Server

We discuss three possible ways to address quantum physics behind chiral magnetic effect and electric charge fluctuation patterns in heavy ion collisions. The first one makes use of P-parity violation probed by local order parameters, the second considers CME in quantum measurement theory framework and the third way is to study P-odd * P-odd contributions to P-even observables. In the latter approach relevant form-factor is extracted and computed for weak magnetic field in confinement region and for free quarks in strong field regime. It is shown that the effect is negligible in the former case. We also discuss saturation effect - charge fluctuation asymmetry for free fermions reaches constant value at asymptotically large fields.

Energy Technology Data Exchange (ETDEWEB)

Hybrid models for solving unit commitment problem have been proposed in this paper. To incorporate the changes due to the addition of new constraints automatically, an expert system (ES) has been proposed. The ES combines both schedules of units to be committed based on any classical or traditional algorithms and the knowledge of experienced power system operators. A solution database, i.e. information contained in the previous schedule is used to facilitate the current solution process. The proposed ES receives the input, i.e. the unit commitment solutions from a fuzzy-neural network. The unit commitment solutions from the artificial neural network cannot offer good performance if the load patterns are dissimilar to those of the trained data. Hence, the load demands, i.e. the input to the fuzzy-neural network is considered as fuzzy variables. To take into account the uncertainty in load demands, a fuzzy decision making ...

International Nuclear Information System (INIS)

In this paper, molecular quantum computation is numerically studied with the quantum search algorithm (Grover's algorithm) by means of optimal control simulation. Qubits are implemented in the vibronic states of I_2, while gate operations are realized by optimally designed laser pulses. The methodological aspects of the simulation are discussed in detail. We show that the algorithm for solving a gate pulse-design problem has the same mathematical form as a state-to-state control problem in the density matrix formalism, which provides monotonically convergent algorithms as an alternative to the Krotov method. The sequential irradiation of separately designed gate pulses leads to the population distribution predicted by Grover's algorithm. The computational accuracy is reduced by the imperfect quality of the pulse design and by the electronic decoherence processes that are modeled by the non-Markovian ...

CERN Document Server

We provide a first-principles, perturbative derivation of the AdS5/CFT4 Y-system that has been proposed to solve the spectrum problem of N=4 SYM. The proof relies on the computation of quantum effects in the fusion of some loop operators, namely the transfer matrices. More precisely we show that the leading quantum corrections in the fusion of transfer matrices induce the correct shifts of the spectral parameter in the T-system. As intermediate steps we study UV divergences in line operators up to first order and compute the fusion of line operators up to second order for the pure spinor string in AdS5xS5. We also argue that the derivation can be easily extended to other integrable models, some of which describe string theory on AdS4, AdS3 and AdS2 spacetimes.

Energy Technology Data Exchange (ETDEWEB)

Recently, the public has become aware of keywords like ''Quantum computer'' or ''Quantum cryptography''. Regarding their potential application in solid state based quantum information processing and their overall benefit in fundamental research quantum dots have gained more and more public interest. In this context, quantum dots are often referred to as ''artificial atoms'', a term subsuming their physical properties quite nicely and emphasizing the huge potential for further investigations. The basic mechanism to be considered is the theoretical model of a two-level system. A quantum dot itself represents this kind of system quite nicely, provided that only the presence or absence of a single exciton in the ground state of that ...

Science.gov (United States)

Recent proposals have shown that a quantum degenerate gas of alkaline earth atoms can be used for a number of novel quantum computing and quantum simulation experiments. Strontium is a good candidate for such experiments because it can be controlled with high precision, as demonstrated in recent atomic clock experiments. Unfortunately, the small scattering length of strontium is not amenable to evaporative cooling techniques that are used to reach quantum degeneracy. Furthermore, increasing the scattering length of alkaline earths with a magnetic Feshbach resonance is not possible due to their spinless electronic ground state configuration. However, recent theoretical and experimental work suggests the possibility of changing scattering lengths in alkaline earths with laser light. Using this optical Feshbach resonance near strontium's narrow ^1S0->^3P1 intercombination transition ...

Energy Technology Data Exchange (ETDEWEB)

Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties. In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be ...

CERN Document Server

We present an application that automatically writes the Helas library corresponding to the Feynman rules of any Lagrangian, renormalizable or not, in quantum field theory. The code, written in Python, takes the Universal FeynRules Output as an input and produces the complete set of routines (wave-functions and amplitudes) that are needed for the computation of Feynman diagrams at leading as well as at higher orders. The representation is language independent and outputs in Fortran, C++, Python are currently available. A few key sample applications implemented in the MadGraph5 framework are presented.

Science.gov (United States)

... This paper presents our research in neural learning for predicting ... Denote this feature set as F4. ... can be observed that the SOC curves generated by ...

International Nuclear Information System (INIS)

This paper is concerned with the real time automatic discriminating of flaws from two categories; i. cracks (planar defect) and ii. Non-cracks (volumetric defect such as cluster porosity and slag) using pulse-echo ultrasound. The raw ultrasonic flaws signal were collected from a computerized robotic plane scanning system over the whole of each reflector as the primary source of data. The signal is then filtered and the analysis in both time and frequency domain were executed to obtain the selected feature. The real time feature analysis techniques measured the number of peaks, maximum index, pulse duration, rise time and fall time. The obtained features could be used to distinguish between quantitatively classified flaws by using various tools in artificial intelligence such as neural networks. The proposed algorithm and complete system were implemented in a computer software developed using Microsoft Visual BASIC 6.0 (author)

British Library Electronic Table of Contents (United Kingdom)

In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. In addition to this, lack of CM can impose a hindrance in electricity trading. This paper presents a novel, growing radial basis function neural network (GRBFNN)-based approach for CM. For achieving CM, Nodal congestion price (NCP) forecasting is performed in real time competitive power market. NCP forecasting is an effective way of price-based preventive CM as it directly indicates the presence as well as the severity of the congestion in the system. In present paper, GRBFNN has been developed for NCP forecasting dividing the whole power system into various congestion zones. An unsupervised learning vector quantization (VQ)...

International Nuclear Information System (INIS)

Computer programs have been written to allow the analysis of different types of eddy-current probes and their performance under different steam generators test conditions. The probe types include the differential bobbin probe, the absolute bobbin probe, the pancake probe and the reflection probe. The generator test conditions include tube supports, copper deposits, magnetite deposits, denting, wastage, pitting, cracking, and intergranular attack. These studies are based mostly on computed values, with the limited number of test specimens available used to verify the computed results. The instrument readings were computed for a complete matrix of the different test conditions, and then the test conditions determined as a function of the readings by a least-squares technique. A comparison was made of the errors in fit and instrument drift for the different probe types. The ...

Science.gov (United States)

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KoreaScience (Korea)

Full Text Available

DEFF Research Database (Denmark)

Udgivelsesdato: 2007/7

Energy Technology Data Exchange (ETDEWEB)

To keep up with the speeds of modern production lines, most machine vision applications require very powerful computers (often parallel-processing machines), which process millions of points of data in real time. The human brain performs approximately 100 billion logical floating-point operations each second. That is 400 times the speed of a Cray-1 supercomputer. The right software must be developed for parallel-processing computers. The NSF has awarded Rensselaer Polytechnic Institute (Troy, N.Y.) a $2 million grant for parallel- and image-processing software research. Over the last 15 years, Rensselaer has been conducting image-processing research, including work with high-definition TV (HDTV) and image coding and understanding. A similar NSF grant has been awarded to Michigan State University (East Lansing, Mich.) Neural networks are supposed to emulate human learning patterns. These networks and their hardware ...

Energy Technology Data Exchange (ETDEWEB)

We propose triplet superconductors, such as ruthenates, as prospective materials for qubit construction. The vectorial nature of the order parameter in triplet superconductors makes it conceptually easy to estimate the performance of the qubits. The Cooper condensate of pairs in triplet superconductors has all the attributes of Bose-Einstein condensates and should facilitate long decoherence times for these qubits, relative to other vectorial schemes for qubits, such as small ferromagnets. There are other benefits, which the superconducting state provides for requirements such as entanglement between qubits via the proximity effect, etc. We consider these benefits in detail, although our consideration is only preliminary and further experimental and theoretical research will undoubtedly introduce correctives.

Energy Technology Data Exchange (ETDEWEB)

We present an efficient parallel algorithm and its implementation for computing the diagonal of $H^-1$ where $H$ is a 2D Kohn-Sham Hamiltonian discretized on a rectangular domain using a standard second order finite difference scheme. This type of calculation can be used to obtain an accurate approximation to the diagonal of a Fermi-Dirac function of $H$ through a recently developed pole-expansion technique \\cite{LinLuYingE2009}. The diagonal elements are needed in electronic structure calculations for quantum mechanical systems \\citeHohenbergKohn1964, KohnSham 1965,DreizlerGross1990. We show how elimination tree is used to organize the parallel computation and how synchronization overhead is reduced by passing data level by level along this tree using the technique of local buffers and relative indices. We analyze the performance of our implementation by examining its load balance and communication overhead. We show that ...

UK PubMed Central (United Kingdom)

Failures in cortical control of fronto-striatal neural circuits may underpin impulsive and compulsive acts. In this narrative review, we explore these behaviors from the perspective of neural processes...Full Text Available

UK PubMed Central (United Kingdom)

Congenital deformities involving the coverings of the nervous system are called neural tube defects (NTDs). NTD can be classified as neurulation defects, which occur by stage 12, and postneurulation...Full Text Available

UK PubMed Central (United Kingdom)

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes...Full Text Available

UK PubMed Central (United Kingdom)

The tendency for some individuals to partake in high-risk behaviors (eg, substance abuse, gambling, risky sexual activities) is a matter of great public health concern, yet the characteristics and neural...Full Text Available

Science.gov (United States)

Adaptive Neural Augmentation , AIAA Guidance, Navigation, and. Control Conference, Aug. 1998. [2] J. T. Kaneshige, J. Bull, and J. J. Totah, Generic Neural ...

International Nuclear Information System (INIS)

A theoretical scheme for quantum secure direct communication (QSDC) is proposed, where a three-qubit symmetric W state functions as a quantum channel. Two legitimate communicators can transmit their secret information by using quantum teleportation and local measurements.

Energy Technology Data Exchange (ETDEWEB)

No abstract prepared.

KoreaScience (Korea)

Full Text Available

International Nuclear Information System (INIS)

The authors present a summary of the present state of the quantum field theory of tachyons. (W.D.L.).

Energy Technology Data Exchange (ETDEWEB)

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformed into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear ...

International Nuclear Information System (INIS)

Ewing's sarcoma is a highly malignant neoplasm of the bone whose origin is still uncertain. A strong relationship exists between Ewing's sarcoma and tumors of neural origin (Ewing family of tumors). Ewing's sarcoma must be distinguished from other round-cell tumors like lymphoma and neuroblastoma and also must be differentiated from osteogenic sarcomas. On plain radiographs, Ewing's sarcoma appears as a lytic or mixed lytic-sclerotic, rarely as predominantly sclerotic lesion with margins Lodwick grade III. It is located primarily in the diaphyseal and metadiaphyseal regions of the long bones of the lower extremities. A large soft tissue tumor is usually present. Magnetic resonance imaging is the imaging modality of choice to evaluate the extent of the primary lesion, to monitor the response to neoadjuvant chemotherapy and to follow up non-resected Ewing's sarcomas. Bone scintigraphy is necessary to detect skeletal metastasis, and "2"0"1thallium scanning has been ...

CERN Document Server

We study from a critical perspective several quantum-electrodynamic phenomena commonly related to vacuum electromagnetic (EM) fluctuations in complex media. We compute the resonance-shift, the spontaneous emission rate, the local density of states and the van-der-Waals-Casimir pressure in a dielectric medium using a microscopic diagrammatic approach. We find, in agreement with some recent works, that these effects cannot be attributed to variations on the energy of the EM vacuum but to variations of the dielectric self-energy. This energy is the result of the interaction of the bare polarizability of the dielectric constituents with the EM fluctuations of an actually polarized vacuum. We have found an exact expression for the spectrum of these fluctuations in a statistically homogeneous dielectric. Those fluctuations turn out to be different to the ones of normal radiative modes. It is the latter that carry the zero-point-energy (ZPE). ...

Energy Technology Data Exchange (ETDEWEB)

We numerically constructed elementary phase-correct global quantum gates by using molecular electronic and vibrational states to encode two qubits and implement the Deutsch-Jozsa algorithm. The calculations were based on optimal control theory (OCT). The molecular species we chose were Na{sub 2} and Li{sub 2}. The electronic X{sup 1}{sigma}{sub g}{sup +} and A{sup 1}{sigma}{sub u}{sup +} states were taken as two orthonormalized energy levels of the electronic qubit. The vibrational qubits were those involved in these electronic states. The time duration of the optimized pulses with high fidelity was typically 500-900 fs, which reflects the wavepacket dynamics in electronically ground and excited states. When implementing the Deutsch-Jozsa algorithm by combining these elementary gates, we obtained a maximum probability 83.12% for Li{sub 2} molecule, which indicates that the electronic-vibrational qubits are worse than the vibrational-vibrational and the ...

Energy Technology Data Exchange (ETDEWEB)

The project aim is to model the hybrid plant at Vaesthamnsverket in Helsingborg using artificial neural networks (ANN) and integrating the ANN models, for online condition monitoring and thermoeconomic optimization, at Vaesthamnsverket. The definition of a hybrid plant is that it uses more than one fuel, in this case a natural gas fuelled gas turbine with heat recovery steam generator (HRSG) and a biomass fuelled steam boiler with steam turbine. The project is a continuation of previous projects where ANN training was done with operational data from the plant. The ANN models have, if required, been updated to better suit the purpose of this project. The thermoeconomic optimization takes into account current electricity prices, taxes, fuel prices etc. and calculates the current production cost along with the 'predicted' production cost. The tool also has a built in feature of predicting when a compressor wash is economically beneficial. The user ...

Energy Technology Data Exchange (ETDEWEB)

In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

Science.gov (United States)

The effects of high-intensity pulsed electromagnetic stimulation (HIPEMS) on proliferation and differentiation of neonatal rat neural stem cells in vitro were investigated. Neural stem cells derived from neonatal rats were exposed to 0.1 Hz, 0.5-10 Tesla (T) [8 groups of B-I, respectively], 5 stimuli of HIPEMF. The sham exposure controls were correspondingly established. Inverted phase contrast microscope was used to observe the cultured cells, MTT assay to detect the viability of the cells as expressed by absorbance (A) value, and flow cytometry to measure differentiation of neural stem cells. The results showed that A values of neural stem cells in both 3.0 T and 4.0 T groups were significantly higher than the other groups 24 to 168 h post HPEMS, indicating a strong promotion of the growth of neural stem cells (PHPEMS groups was the same as that in control group (P>0.05). It ...

CERN Document Server

We study N=2 SuperVirasoro SCFT for the generic value of the central charge. The main tool is the nonstandard bosonisation suggested in \\ref\\rRoz{L. Rozansky a letter to M. Bershadsky, 1989}, \\ref\\rSeBGR{B. Gato-Rivera, A. Semikhatov Phys. Letts. B293 (1992) 72},\\ref\\rBLNW{M. Bershadsky, W. Lerche, D. Nemeshansky, N. Warner N=2 Extended superconformal structure of Gravity and W Gravity coupled to Matter HUTP-A034/92}. The free field resolutions for the irreducible representations are obtained; the characters of these representations are computed. The quantum hamiltonian reduction from the Kac-Moody $\\hat{sl}_k(2|1)$ to N=2 $SVir$ is constructed.

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Methylation of the DNA bases in the Watson-Crick GC and AT base pairs by the methyldiazonium ion was investigated employing density functional and second order Moller-Plesset (MP2) perturbation theories. Methylation at the N3, N7 and O6 sites of guanine, N1, N3 and N7 sites of adenine, O2 and N3 sites of cytosine and the O2 and O4 sites of thymine were considered. The computed reactivities for methylation follow the order N7(guanine)>N3(adenine)>O6(guanine) which is in agreement with experiment. The base pairing in DNA is found to play a significant role with regard to reactivities of the different sites.

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For InAs-GaAs based quantum dot lasers emitting at 1300 nm, digital modulation showing an open eye pattern up to 12 Gb s{sup -1} at room temperature is demonstrated, at 10 Gb s{sup -1} the bit error rate is below 10{sup -12} at -2 dB m receiver power. Cut-off frequencies up to 20 GHz are realised for lasers emitting at 1.1 {mu}m. Passively mode-locked QD lasers generate optical pulses with repetition frequencies between 5 and 50 GHz, with a minimum Fourier limited pulse length of 3 ps. The uncorrelated jitter is below 1 ps. We use here deeply etched narrow ridge waveguide structures which show excellent performance similar to shallow mesa structures, but a circular far field at a ridge width of 1 {mu}m, improving coupling efficiency into fibres. No beam filamentation of the fundamental mode, low a-factors and strongly reduced sensitivity to optical feedback are observed. QD lasers are thus superior to QW lasers for any system or network. ...

CERN Document Server

In order to describe quantum heat engines, here we systematically study isothermal and isochoric processes for quantum thermodynamic cycles. Based on these results the quantum versions of both the Carnot heat engine and the Otto heat engine are defined without ambiguities. We also study the properties of quantum Carnot and Otto heat engines in comparison with their classical counterparts. Relations and mappings between these two quantum heat engines are also investigated by considering their respective quantum thermodynamic processes. In addition, we discuss the role of Maxwell's demon in quantum thermodynamic cycles. We find that there is no violation of the second law, even in the existence of such a demon, when the demon is included correctly as part of the working substance of the heat engine.

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How much information is stored in the ground-state of a system without \\emph{any symmetry} and how can we extract it? This question is investigated by analyzing the behavior of a topological Chern Insulator (CI) in the presence of disorder, with a focus on its entanglement spectrum (EtS) constructed from the ground state. For systems with symmetries, the EtS was shown to contain explicit information revealed by sorting the EtS against the conserved quantum numbers. In the absence of any symmetry, we demonstrate that statistical methods such as the level statistics of the EtS can be equally insightful, allowing us to distinguish when an insulator is in a topological or trivial phase and to map the boundary between the two phases, where EtS becomes entirely delocalized. The phase diagram of a CI is explicitly computed as function of Fermi level ($E_F$) and disorder strength using the level statistics of the EtS and energy spectrum (EnS), ...

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Transforming growth factor beta (TGF-@b) has a crucial role in the differentiation of ectodermal cells to neural or epidermal precursors. TGF-@b and bone morphogenetic protein molecules (BMPs) are involved in many developmental processes, including cell proliferation and differentiation, apoptosis, mitotic arrest and intercellular interactions during morphogenesis. Additionally, the failure of central thymic tolerance mechanisms, leading to T cells with a skewed autoreactive response, is being described as a contributor in inflammatory processes in autoimmune diseases such as multiple sclerosis. Since TGF-@b and BMP proteins are crucial for the development of the neural system and the thymus, as well as for the differentiation of T cells, it is essential to further investigate their role i...

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Superheater corrosion causes vast annual losses to the power companies. If the corrosion could be reliably predicted, new power plants could be designed accordingly, and knowledge of fuel selection and determination of process conditions could be utilized to minimize superheater corrosion. If relations between inputs and the output are poorly known, conventional models depending on corrosion theories will fail. A prediction model based on a neural network is capable of learning from errors and improving its performance as the amount of data increases. The neural network developed during this study predicts superheater corrosion with 80 % accuracy at early stage of the project. (orig.) 10 refs.

International Nuclear Information System (INIS)

Supplementing the collection of artificial neural network methodologies devised for monitoring energy producing installations, a general regression artificial neural network is proposed for the identification of the two-phase flow that occurs in the coolant channels of boiling water reactors. The utilization of a limited number of image features derived from radiography images affords the proposed approach with efficiency and non-invasiveness. Additionally, the application of counter-clustering to the input patterns prior to training accomplishes an 80% reduction in network size as well as in training and test time. Cross-validation tests confirm accurate on-line flow regime identification.

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Werner states are paradigmatic examples of quantum states and play an innovative role in quantum information theory. In investigating the correlating capability of Werner states, we find the curious phenomenon that quantum correlations, as quantified by the entanglement of formation, may exceed the total correlations, as measured by the quantum mutual information. Consequently, though the entanglement of formation is so widely used in quantifying entanglement, it cannot be interpreted as a consistent measure of quantum correlations per se if we accept the folklore that total correlations are measured (or rather upper bounded) by the quantum mutual information.

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A back-propagation neural network technique is used at JET to extract plasma parameters like ion temperature, rotation velocities or spectral line intensities from charge exchange (CX) spectra. It is shown that in the case of the C VI CX spectra, neural networks can give a good estimation (better than +-20% accuracy) for the main plasma parameters (Ti, V{sub rot}). Since the neural network approach involves no iterations or initial guesses the speed with which a spectrum is processed is so high (0.2 ms/spectrum) that real time analysis will be achieved in the near future. 4 refs., 8 figs.

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Because the state of a free-floating space robot model is uncertain and sudden changes in the model parameters might undermine the stability of the system, this paper proposes a control strategy based on a variable structure neural integrated controller. This scheme does not need a precise space robot model, making use of the radial basis function neural network ability approach to learn about an uncertain model. The network weights are adjusted online in real-time. During the early period of the control phase and parameter changes, the variable structure controller compensates for the uncertain model which the neural network could not learn well. It also creates global asymptotic stability for the whole closed-loop system. Simulation results show that the controller can handle bad changea...

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[9] Rysdyk, R. T., and Calise, A. J., Fault Tolerant Flight control via Adaptive Neural Augmentation, AIAA. Guidance, Navigation, and Control Conference, Aug. ...

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A new recurrent neural network power system stabilizer (RNNPSS) based on genetic algorithm (GA) was presented. It shows faster convergence than the linear quadratic regulator (LQR) stabilizer in a multi-machine power system, because the proposed GA based neural network was first trained off-line to determine the optimal values of the learning rates. Otherwise, the RNNPSS consists of just two layers. As such, the time consumption of the damping oscillations is lower than with conventional methods. In addition, the operating range of the RNNPSS is greater than that of the LQR and conventional three layer neural networks, since the RNNPSS can greatly reduce system complexity and effectively damp system oscillations. 9 refs., 7 figs.

CERN Document Server

Theory of quantum games is relatively new to the literature and its applications to various areas of research are being explored. It is a novel interpretation of strategies and decisions in quantum domain. In the earlier work on quantum games considerable attention was given to the resolution of dilemmas present in corresponding classical games. Two separate quantum schemes were presented by Eisert et al. and Marinatto and Weber to resolve dilemmas in Prisoners' Dilemma and Battle of Sexes games respectively. However for the latter scheme it was argued that dilemma was not resolved. We have modified the quantization scheme of Marinatto and Weber to resolve the dilemma. We have developed a generalized quantization scheme for two person non-zero sum games which reduces to the existing schemes under certain conditions. Applications of this generalized quantization scheme to quantum ...

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At the occasion of the OECS conference in Madrid, we give a succinct account of some recent predictions in the spectroscopy of a quantum dot in a microcavity that remain to be observed experimentally, sometimes within the reach of the current state of the art.

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A process has been proposed to increase the efficiency of an ideal Otto cycle via a quantum heat engine that has no cooler reservoir. We show that such a process is not feasible.

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Feb 13, 2005 ... Part 8 of a non-mathematical historical review of elementary quantum theory, to help explain processes in the Sun and in stars; part of an ...

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In this paper we propose a method for construction of feed-forward neural classifiers based on regularization and adaptive architectures. Using a penalized maximum likelihood scheme, we derive a modified form of the entropic error measure and an algebraic estimate of the test error. In conjunction with optimal brain damage pruning, a test error estimate is used to select the network architecture. The scheme is evaluated on four classification problems. PMID:12662736

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We define the Bloch spectrum of a quantum graph to be the collection of the spectra of a family of Schr\\"odinger operators parametrized by the cohomology of the quantum graph. We show that the Bloch spectrum determines the Albanese torus, the block structure and the planarity of the graph. It determines a geometric dual of a planar graph. This enables us to show that the Bloch spectrum completely determines planar 3-connected quantum graphs.

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We discuss the use of active control to reduce mirror position fluctuations at the quantum level. We have shown in a recent experiment that it is possible to reduce the thermal noise of a mirror by measuring and controlling its motion with an optomechanical sensor based on a high-finesse optical cavity. This approach can be extended to lock the mirror motion at the quantum level, and to suppress the quantum effects of radiation pressure in interferometric measurements such as gravitational-wave detectors. The sensitivity improvement is furthermore independent of losses in the interferometer.

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We study the possibility of utilizing the superfluid to Mott-insulator quantum phase transition in an array of quantum well exciton-polariton traps to generate indistinguishable single photons in a massive parallel fashion. By means of analytical and numerical methods, the device operations and system properties are examined using realistic experimental parameters. Such a deterministic, massive parallel generation may find new applications in photonic quantum information processing.

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The loop quantum cosmology 'improved dynamics' of the Bianchi type IX model are studied. The action of the Hamiltonian constraint operator is obtained via techniques developed for the Bianchi type I and type II models, no new input is required. It is shown that the big bang and big crunch singularities are resolved by quantum gravity effects. We also present effective equations which provide quantum geometry corrections to the classical equations of motion.

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This report discusses whether the events that occur in the universe evolve deterministicly or randomly or both. (LSP).

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Target recognition requires the ability to distinguish targets from non-targets, a capability called one-class generalization. Many neural network pattern classifiers fail as one-class classifiers because they use open decision boundaries. To function as one-class classifier, a neural network must have three types of generalization: within-class, between-class, and out-of-class. We discuss these three types of generalization and identify neural network architectures that meet these requirements. We have applied our one-class classifier ideas to the problem of automatic target recognition in synthetic aperture radar. We have compared three neural network algorithms: Carpenter and Grossberg`s algorithmic version of the Adaptive Resonance Theory (ART-2A), Kohonen`s Learning Vector Quantization (LVQ), and Reilly and Cooper`s Restricted Coulomb Energy network (RCE). The ART 2-A neural ...

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Recently it was demonstrated that long-lived quantum coherence exists during excitation energy transport in photosynthesis. It is a valid question up to which length, time and mass scales quantum coherence may extend, how one may detect this coherence and what, if any, role it plays in the dynamics of the system. Here we suggest that the selectivity filter of ion channels may exhibit quantum coherence, which might be relevant for the process of ion selectivity and conduction. We show that quantum resonances could provide an alternative approach to ultrafast two-dimensional (2D) spectroscopy to probe these quantum coherences. We demonstrate that the emergence of resonances in the conduction of ion channels that are modulated periodically by time-dependent external electric fields can serve as signatures of quantum coherence in such a system. Assessments of ...

CERN Document Server

Very recently we have assisted to a new development of quantum information, the so-called continuous variable (CV) quantum information theory. Such a further development has been mainly due to the experimental and theoretical advantages offered by CV systems, i.e., quantum systems described by a set of observables, like position and momentum, which have a continuous spectrum of eigenvalues. According to this novel trend, quantum information protocols like quantum teleportation have been suitably extended to the CV framework. Here, we briefly review some mathematical tools relative to CV systems and we consequently develop the concepts of quantum entanglement and teleportation in the CV framework, by analogy with the qubit-based approach. Some connections between teleportation fidelity and entanglement properties of the underlying quantum ...

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The influence of carbon monoxide (CO) exposure on regional cerebral blood flow (r-CBF) in rat brain was studied using autoradiography and "1"2"5I-IMP. Fuji computed radiography (FCR) was used to obtain improved autoradiograms in this study. R-CBF was determined in a relative measure by calculating hippocampus/cortex and putamen/cortex ratios of RI accumulation from the autoradiogram using a densitometer. Comparison of autoradiograms with pathological findings in the area of the hippocampus and putamen yield the following results. In the animals that were exposed to 6400 ppm or 10000 ppm of CO for 30 minutes, and then were followed up for 2 weeks without further exposure, r-CBF was decreased but no pathological changes occurred. In the animals that were exposed to 6400 ppm or 10000 ppm of CO, and then were followed up for 4 weeks without further exposure, pathological changes appeared. In animals exposed to 3200 ppm of CO, the r-CBF tended to recover after 4 weeks. ...

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The wavefunction of a particle extends into the classically forbidden barrier region of the potential energy surface. The consequence of this partial delocalisation is the phenomenon of quantum tunnelling, an effect which enables a particle to penetrate a potential barrier of magnitude greater than the energy of the particle. The tunnelling probability is an exponential function of the particle mass. The effect is therefore an important contribution to the behaviour of light atoms, in particular the proton. The hydrogen bond has long been appreciated to be an essential component of many biological and chemical systems, and the proton transfer reaction in the hydrogen bond is fundamental to many of these processes. The proton behaviour in the hydrogen bonds of benzoic acid, acetylacetone and calix-4-arene has been studied. A variety of techniques, both experimental and computational, were adopted for the study of the three hydrogen bonded ...

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We study free and self-interacting scalar quantum field theories in a flat Robertson-Walker metric in the functional Schroedinger picture. We discuss Schroedinger picture quantization, relating it to conventional Heisenberg picture quantization. For the interacting theory, we introduce the time-dependent Gaussian approximation to study time evolution of pure and mixed states and we establish renormalizability of the approximation. We also study the question of computing a finite, renormalized energy-momentum tensor for both the free and the interacting theory in the Gaussian appproximation. Using the adiabatic expansion, we show that the entire subtration necessary to make the the energy-momentum tensor finite in the free theory can be written in terms of covariantly conserved tensors. We further show that the same subtraction is sufficient to make the energy-momentum tensor finite in the Gaussian approximation for the interacting theory ...

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Due to the increased computer power and advanced algorithms, quantum mechanical calculations based on Density Functional Theory are more and more widely used to solve real materials science problems. In this context large nonlinear generalized eigenvalue problems must be solved repeatedly to calculate the electronic ground state of a solid or molecule. Due to the nonlinear nature of this problem, an iterative solution of the eigenvalue problem can be more efficient provided it does not disturb the convergence of the self-consistent-field problem. The blocked Davidson method is one of the widely used and efficient schemes for that purpose, but its performance depends critically on the preconditioning, i.e. the procedure to improve the search space for an accurate solution. For more diagonally dominated problems, which appear typically for plane wave based pseudopotential calculations, the inverse of the diagonal of (H - ES) is used. However, for ...

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A stable power system stabilizer (PSS) based on the inverse dynamics of the controlled system using an artificial neural network (ANN) is suggested to enhance the dynamic performances of a power system. First, an output feedback control law is driven with some conditions satisfied, which guarantees the internal stability and robustness against the asymptotically stable external disturbances. Then the control law is implemented using the inverse dynamics of the controlled plant. The inverse dynamics of the controlled plant is identified by an ANN, inverse dynamics neural network (IDNN), off-line. The pole-shifting technique and a scaling factor are introduced for the control system to meet the conditions for internal stability and robustness. The proposed controller is applied to a typical single-machine infinite-bus power system. Simulation results under various operation conditions are given which show that the proposed controller damps the ...

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Timely detection of the pneumatic system problems is important in industry. Many techniques have been employed to solve this problem. In this paper, Genetic Algorithm (GA) based optimal configuration of neural networks is proposed for fault diagnostic of bottle filling systems. Back-propagation is used for neural networks algorithm. The back-propagation algorithm had six inputs and one output. A fitness function was designed to the minimize execution time of ANN model by keeping the number of hidden layer(s) and nodes as low as possible while the mean square error of estimated output error is minimized. The designed GA-ANN combination and the graphical user interface (GUI) eliminate the trial and error process for selection of the fastest and most accurate configuration. The performance of...

CERN Document Server

We consider the effect of distributed delays in neural feedback systems. The avian optic tectum is reciprocally connected with the nucleus isthmi. Extracellular stimulation combined with intracellular recordings reveal a range of signal delays from 4 to 9 ms between isthmotectal elements. This observation together with prior mathematical analysis concerning the influence of a delay distribution on system dynamics raises the question whether a broad delay distribution can impact the dynamics of neural feedback loops. For a system of reciprocally connected model neurons, we found that distributed delays enhance system stability in the following sense. With increased distribution of delays, the system converges faster to a fixed point and converges slower toward a limit cycle. Further, the introduction of distributed delays leads to an increased range of the average delay value for which the system's equilibrium point is stable. The enhancement of ...

CERN Document Server

Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back propagation neural (BPN) network has been applied successfully in many areas with excellent generalization results, such as rule extraction, classification and evaluation. In this paper, a model based on SVM with Gaussian RBF kernel is proposed here for enterprise financial distress evaluation. BPN network is considered one of the simplest and are most general methods used for supervised training of multilayered neural network. The comparative results show that through the difference between the performance measures is marginal; SVM gives higher precision and lower error rates.

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In this paper, a neural networks (NN) based adaptive sliding mode controller (SMC) is introduced. The selection of SMC feedback gains is normally based on one operating point and thus the performance of the controller away from the design operating point is, of necessity, a compromise. The adaptive SMC is proposed to overcome the limitations imposed on the effectiveness of the SMC under different operating conditions. Neural networks are used for online prediction of the optimal SMC gains when the operating point changes. The proposed method has been applied to a power system stabilizer (PSS) of a single machine power system. Simulation results are included to demonstrate the performance of the proposed control scheme.

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We present a quantum secure direct communication scheme achieved by swapping quantum entanglement. In this scheme a set of ordered Einstein-Podolsky-Rosen (EPR) pairs is used as a quantum information channel for sending secret messages directly. After insuring the safety of the quantum channel, the sender Alice encodes the secret messages directly by applying a series local operations on her particle sequences according to their stipulation. Using three EPR pairs, three bits of secret classical information can be faithfully transmitted from Alice to remote Bob without revealing any information to a potential eavesdropper. By both Alice and Bob's GHZ state measurement results, Bob is able to read out the encoded secret messages directly. The protocol is completely secure if perfect quantum channel is used, because there is not a transmission of the qubits carrying the secret message ...

CERN Document Server

A fully consistent linear perturbation theory for cosmology is derived in the presence of quantum corrections as they are suggested by properties of inverse volume operators in loop quantum gravity. The underlying constraints present a consistent deformation of the classical system, which shows that the discreteness in loop quantum gravity can be implemented in effective equations without spoiling space-time covariance. Nevertheless, non-trivial quantum corrections do arise in the constraint algebra. Since correction terms must appear in tightly controlled forms to avoid anomalies, detailed insights for the correct implementation of constraint operators can be gained. The procedures of this article thus provide a clear link between fundamental quantum gravity and phenomenology.

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The performance of 250 different computational protocols (combinations of density functionals, basis sets and methods) was assessed on a set of 165 well-established experimental (1)H-(1)H nuclear coupling constants (J(H-H)) from 65 molecules spanning a wide range of "chemical space". Thereby we found that, if one uses core-augmented basis sets and allows for linear scaling of the raw results, calculations of only the Fermi contact term yield more accurate predictions than calculations where all four terms that contribute to J(H-H) are evaluated. It turns out that B3LYP/6-31G(d,p)u+1s is the best (and, in addition, one of the most economical) of all tested methods, yielding predictions of J(H-H) with a root-mean-square deviation from experiment of less than 0.5 Hz for our test set. Another method that does similarly well, without the need for additional 1s basis functions, is B3LYP/cc-pVTZ, which is, however, ca. 8 times more "expensive" in terms of CPU time. A ...

UK PubMed Central (United Kingdom)

During development, multipotent neural precursors give rise to oligodendrocyte progenitor cells (OPCs), which migrate and divide to produce additional OPCs. Near the end of embryogenesis and...Full Text Available

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The central nervous system regulates peripheral immune responses via the vagus nerve, the primary neural component of the cholinergic anti-inflammatory pathway. Electrical stimulation of the...Full Text Available

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BackgroundThe variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing...Full Text Available

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In this paper, the combustible value (i.e. 100-Ash) and combustible recovery of coal flotation concentrate were predicted by regression and artificial neural network based on proximate and group macerals analysis. The regression method shows that the relationships between (a) in (ash), volatile matter and moisture (b) in (ash), in (liptinite), fusinite and vitrinite with combustible value can achieve the correlation coefficients (R{sup 2}) of 0.8 and 0.79, respectively. In addition, the input sets of (c) ash, volatile matter and moisture (d) ash, liptinite and fusinite can predict the combustible recovery with the correlation coefficients of 0.84 and 0.63, respectively. Feed-forward artificial neural network with 6-8-12-11-2-1 arrangement for moisture, ash and volatile matter input set was capable to estimate both combustible value and combustible recovery with correlation of 0.95. It was shown that the proposed neural ...

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Percutaneous radiofrequency ablation is the treatment of choice for osteoid osteoma of the appendicular skeleton. However, difficulties in localizing the lesion in the spine and its proximity to neural...Full Text Available

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Target recognition requires the ability to distinguish targets from non-targets, a capability called one-class generalization. To function as a one-class classifier, a neural network must have three types of generalization: within-class, between-class, and out-of-class. We discuss these three types of generalization and identify neural network architectures that meet these requirements. We have applied our one-class classifier ideas to the problem of automatic target recognition in synthetic aperture radar. We have compared three neural network algorithms: Carpenter and Grossberg`s algorithmic version of the Adaptive Resonance Theory (ART-2A), Kohonen`s Learning Vector Quantization (LVQ), and Reilly and Cooper`s Restricted Columb Energy network (RCE). The ART 2-A neural network has given the best results, with 100% within-class, and out-of-class generalization. Experiments show that the network`s ...

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The CNS can exhibit features of inflammation in response to injury, infection or disease, whereby resident cells generate inflammatory mediators, including cytokines, prostaglandins, free radicals and...Full Text Available

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An optical flow gradient algorithm was applied to spontaneously forming networks of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling...Full Text Available

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An influential neural model of face perception suggests that the posterior superior temporal sulcus (STS) is sensitive to those aspects of faces that produce transient visual changes, including facial...Full Text Available

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Synaptic gain control and information storage in neural networks are mediated by alterations in synaptic transmission, such as in long-term potentiation (LTP). Here, we show using both in...Full Text Available

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A prevailing theory proposes that the brain's two visual pathways, the ventral and dorsal, lead to differing visual processing and world representations for conscious perception than those for action....Full Text Available

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Humans are remarkably adept at identifying individuals by the sound of their voice, a behavior supported by the nervous system’s ability to integrate information from voice and speech...Full Text Available

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BackgroundWax esters are important ingredients in cosmetics, pharmaceuticals, lubricants and other chemical industries due to their excellent wetting property. Since the naturally...Full Text Available

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Stem cell therapies for neurodegenerative disorders require accurate delivery of the transplanted cells to the sites of damage. Numerous studies have established that fluid injections to the hippocampus...Full Text Available

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The neuromodulatory function of dopamine (DA) is an inherent feature of nervous systems of all animals. To learn more about the function of neural DA in Drosophila, we generated mutant...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific ...

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Several efforts have been made to completely automate cephalometric analysis by automatic landmark search. However, accuracy obtained was worse than manual identification in every study. The analogue-to-digital...Full Text Available

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This work presents a digital adaptive Power System Stabilizer (PSS) which operates in a gain scheduling scheme. It`s parameters are designed for a lot of different operating regions in a P x Q plane (active and reactive powers), and saved in a microcomputer real time control. During working, the PSS identifies the present region of operation, and synthesizes its damping signal in accordance with the parameters for that region. As an extension of the method, a neural PSS, which uses the set of parameters of each region as a standard set to train a neural network to form this PSS, is also proposed. The tests presented show good performance for both PSS, when compared to a conventional (non adaptive) one. (author) 10 refs., 5 figs., 1 tab.; e-mail: jalb at guama.cpgee.ufpa.br

International Nuclear Information System (INIS)

Using a new approach to quaternion mechanics based on De Broglie waves, it is shown that such a theory describes tachyons and that the quantum theory of tachyons should be a quaternionic one. (U.K.).

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We obtain a symmetry algebra for any unitary minimal model by using the representation of conformal field theories. This symmetry algebra can be interpreted as a quantum group. The generalization to non-unitary minimal models is direct. (orig.).

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In this paper method of constructing quasi-exactly solvable models of quantum mechanics is proposed. This method is based on the use of infinite-dimensional representations of simple and semi-simple Lie algebras.

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A controlled bidirectional quantum secret direct communication scheme is proposed by using a Greenberger-Horne-Zeilinger (GHZ) state. In the scheme, two users can exchange their secret messages simultaneously with a set of devices under the control of a third party. The security of the scheme is analysed and confirmed.

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We review visually guided behaviors in larval zebrafish and summarise what is known about the neural processing that results in these behaviors, paying particular attention to the progress made in the last 2 years. Using the examples of the optokinetic reflex, the optomotor response, prey tracking and the visual startle response, we illustrate how the larval zebrafish presents us with a very promising model vertebrate system that allows neurocientists to integrate functional and behavioral studies and from which we can expect illuminating insights in the near future.

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Artificial Neural Networks (ANNs) are parallel distributed processing machines. The unique characteristics of ANNs are: Fault tolerance, robustness, plasticity and generalization. These offer great potential in many AI applications such as character recognition. Handwritten character recognition is an intrinsically interesting problem, but the difficulties of this task are the many variations in the characters. A robust new incremental learning method, which combines supervised and unsupervised learning paradigms implemented by the Functional Link Net, is illustrated with experimental results. Clustering, based on unsupervised learning, classifies the input data into several categories. The supervised learning paradigm then further classifies the data in the clustered categories.

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In this paper an attempt is made to forecast load using fuzzy neural network (FNN) for an integrated power system. Here, the proposed system uses a two stage FNN for a short term peak and average load forecasting (STPALF). The first stage FNN deals with the load forecasting and the second stage algorithm can be worked independently for network security. This technique is used to forecast load accurately on week days as well as holidays, weekends and some special occasions considering historical data of load and weather information and also take necessary control action for network security.

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This paper deals with an artificial neural network (ANN) based adaptive conventional power system stabilizer (PSS). The ANN comprises an input layer, a hidden layer and an output layer. The input vector to the ANN comprises real power (P) and reactive power (Q), while the output vector comprises optimum PSS parameters. A systematic approach for generating training set covering wide range of operating conditions, is presented. The ANN has been trained using back-propagation training algorithm. Investigations reveal that the dynamic performance of ANN based adaptive conventional PSS is quite insensitive to wide variations in loading conditions.

International Nuclear Information System (INIS)

Two avowable quantum communication schemes are proposed. One is an avowable teleportation protocol based on the quantum cryptography. In this protocol one teleports a set of one-particle states based on the availability of an honest arbitrator, the keys and the Einstein-Podolsky-Rosen pairs shared by the communication parties and the arbitrator. The key point is that the fact of the teleportation can neither be disavowed by the sender nor be denied by the receiver. Another is an avowable quantum secure direct communication scheme. A one-way Hash function chosen by the communication parties helps the receiver to validate the truth of the information and to avoid disavowing for the sender.

International Nuclear Information System (INIS)

The conventional treatment of quantum field theories including tachyons is presented, in particular the phi"4 theory. (W.D.L.).

International Nuclear Information System (INIS)

... dpg-tagungen.de Dresden (Germany) 27-31 Mar 2006 0420-0195 VDPEAZ

Science.gov (United States)

In this paper, we proposed a novel quantum secure direct communication scheme with one-time pad in stabilizer formalism. Based on the reuse of qubit sequence, an efficient secure communication of secret messages without first producing a shared secret key can be achieved. One hence may find that the amount of private key needed for quantum communication is smaller than that in the general case. Therefore, the present protocol which is feasible with the present-day techniques may be applied to quantum communication with short-length encoding.

CERN Document Server

We study the all-optical time-control of the strong coupling between a single cascade three-level quantum emitter and a microcavity. We find that only specific arrival-times of the control pulses succeed in switching-off the Rabi oscillations. Depending on the arrival times of control pulses, a variety of exotic non-adiabatic cavity quantum electrodynamics effects can be observed. We show that only control pulses with specific arrival times are able to suddenly switch-off and -on first-order coherence of cavity photons, without affecting their strong coupling population dynamics. Such behavior may be understood as a manifestation of quantum complementarity.

International Nuclear Information System (INIS)

The propriety of the cosmic no-hair conjecture to the Bianchi-type-IX spacetime is discussed from a quantum cosmological point of view. It is shown that most, but not all, classical universes which are created quantum cosmologically are inflationary. The probability of inflation among such universes is also discussed.

International Nuclear Information System (INIS)

X-ray scattering methods suitable for the investigation of the morphology and chemical composition of self-organized quantum dots and quantum wires are reviewed. Their application is demonstrated in experimental examples showing that a combination of small angle X-ray scattering with high-resolution X-ray diffraction can reveal both the shape and the chemical composition of the self-organized objects. (author)

CERN Document Server

We report the first experimental generation and characterization of a six-photon Dicke state and demonstrate its remarkable versatility by projecting out four- and five-photon Dicke states, in addition to four-photon GHZ- and W-states. These multipartite states are studied by developing experimentally favorable characterization tools. Furthermore, we show that Dicke states have interesting applications in multiparty quantum networking protocols such as open-destination teleportation, telecloning and quantum secret sharing.

CERN Document Server

We present a strong-weak coupling duality for quantum mechanical potentials. Similarly to what happens in quantum field theory, it relates two problems with inverse couplings, leading to a mapping of the strong coupling regime into the weak one, giving information from the nonperturbative region of the parameters space. It can be used to solve exactly power-type potentials and to extract deep information about the energy spectra of polynomial ones. We present a strong-weak coupling duality for quantum mechanical potentials. Similarly to what happens in quantum field theory, it relates two problems with inverse couplings, leading to a mapping of the strong coupling regime into the weak one, giving information from the nonperturbative region of the parameters space. It can be used to solve exactly power-type potentials and to extract deep information about the energy spectra of polynomial ones.

CERN Document Server

The unavoidable irreversible losses of power in a heat engine are found to be of quantum origin. Following thermodynamic tradition a model quantum heat engine operating by the Otto cycle is analyzed. The working medium of the model is composed of an ensemble of harmonic oscillators. A link is established between the quantum observables and thermodynamical variables based on the concept of canonical invariance. These quantum variables are sufficient to determine the state of the system and with it all thermodynamical variables. Conditions for optimal work, power and entropy production show that maximum power is a compromise between the quasistatic limit of adiabatic following on the compression and expansion branches and a sudden limit of very short time allocation to these branches. At high temperatures and quasistatic operating conditions the efficiency at maximum power coincides with the ...

CERN Document Server

Bargmann's superselection rule, which forbids the existence of superpositions of states with different mass and, therefore, implies the impossibility of describing unstable particles in non-relativistic quantum mechanics, arises as a consequence of demanding Galilean covariance of Schr\\"odinger's equation. However, the usual Galilean transformations inadequately describe the symmetries of non-relativistic quantum mechanics since they fail to take into account relativistic time contraction effects which can produce non-relativistic phases in the wavefunction. In this paper we describe the incompatibility between Bargmann's rule and Lorentz transformations in the low-velocities limit, we analyze its classical origin and we show that the Extended Galilei group characterizes better the symmetries of the theory. Furthermore, we claim that a proper description of non-relativistic quantum mechanics requires a modification of the ...

Science.gov (United States)

Jun 16, 2011 ... The research is part of a team effort to help the hardwood sawmill industry automate with computer vision systems, and computer-aided or ...

Energy Technology Data Exchange (ETDEWEB)

The construction of networks consisting of optically interconnected processing units is a promising way to scale up quantum information processing systems. To store quantum information, single trapped atoms are among the most proven candidates. By placing them in high finesse optical resonators, a bidirectional information exchange between the atoms and photons becomes possible with, in principle, unit efficiency. Such an interface between stationary and ying qubits constitutes a possible node of a future quantum network. The results presented in this thesis demonstrate the prospects of a quantum interface consisting of a single atom trapped within the mode of a high-finesse optical cavity. In a two-step process, we distribute entanglement between the stored atom and two subsequently emitted single photons. The long atom trapping times achieved in the system together with the high photon collection ...

Energy Technology Data Exchange (ETDEWEB)

Temperature and concentration profiles of CO in a laminar, axisymmetric, premixed methane-air Bunsen flame are measured using line-of-sight diode laser absorption spectroscopy and computer tomographic (CT) reconstruction. Absorption spectra for P(20) (v=2<-1) and P(27) (v=1<-0) vibrotational transitions of CO were measured at 21 evenly spaced positions over a 1.33 cm span for a 1.3 cm radius flame. CT reconstruction algorithm was based on Fourier convolution. The tomographically reconstructed normalized transmission profiles derived from absorption spectra, in conjunction with a quantum mechanical model for vibrotational behavior of CO, yielded both temperature and concentration profiles. The Bunsen flame had 3 distinct zones: an inner rich-premixed flame zone, an outer non-premixed flame zone and an unburnt core region. The reconstructed temperature profile showed that the core region temperature was close to ambient and rapidly ...

Energy Technology Data Exchange (ETDEWEB)

We find that tachyonic orbifold examples of AdS/CFT have corresponding instabilities at small radius, and can decay to more generic gauge theories. We do this by computing a destabilizing Coleman-Weinberg effective potential for twisted operators of the corresponding quiver gauge theories, generalizing calculations of Tseytlin and Zarembo and interpreting them in terms of the large-N behavior of twisted-sector modes. The dynamically generated potential involves double-trace operators, which affect large-N correlators involving twisted fields but not those involving only untwisted fields, in line with large-N inheritance arguments. We point out a simple reason that no such small radius instability exists in gauge theories arising from freely acting orbifolds, which are tachyon-free at large radius. When an instability is present, twisted gauge theory operators with the quantum numbers of the large-radius tachyons acquire VEVs, leaving a gauge ...

Energy Technology Data Exchange (ETDEWEB)

Results from ultimate analysis, proximate and petrographic analyses of a wide range of Kentucky coal samples were used to predict coal rank parameters (vitrinite maximum reflectance (R{sub max}) and gross calorific value (GCV)) using multivariable regression and artificial neural network (ANN) methods. Volatile matter, carbon, total sulfur, hydrogen and oxygen were used to predict both R{sub max} and GCV by regression and ANN. Multivariable regression equations to predict R{sub max} and GCV showed R{sup 2} = 0.77 and 0.69, respectively. Results from the ANN method with a 2-5-4-2 arrangement that simultaneously predicts GCV and R{sub max} showed R{sup 2} values of 0.84 and 0.90, respectively, for an independent test data set. The artificial neural network method can be appropriately used to predict R{sub max} and GCV when regression results do not have high accuracy. (author)

Energy Technology Data Exchange (ETDEWEB)

To determine if barbiturates would protect brain at high doses of radiation, survival rates in rats that received whole-brain x-irradiation during pentobarbital- or lidocaine-induced anesthesia were compared with those of control animals that received no medication and of animals anesthetized with ketamine. The animals were shielded so that respiratory and digestive tissues would not be damaged by the radiation. Survival rates in rats that received whole-brain irradiation as a single 7500-rad dose under pentobarbital- or lidocaine-induced anesthesia was increased from between from 0% and 20% to between 45% and 69% over the 40 days of observation compared with the other two groups (p less than 0.007). Ketamine anesthesia provided no protection. There were no notable differential effects upon non-neural tissues, suggesting that pentobarbital afforded protection through modulation of ambient neural activity during radiation exposure. ...

Energy Technology Data Exchange (ETDEWEB)

We revisited the quantum Zeno paradox, which claims that a generic quantum system prepared in a state which is not an eigenstate of the Hamiltonian operator and is continuously observed never decays. Since any perfectly isolated quantum system always interact with a vacuum field, we analyze the possibility of using this fact to solve the above mentioned conceptual problem. Therefore we discuss a two-level system or qubit-Bose field interaction Hamiltonians. We consider the quantum dynamics of this two-level system, prepared in the excited state interacting with a Bose field prepared in the Poincare invariant vacuum state. Using a first-order approximation in time-dependent perturbation theory, we evaluate the probability of spontaneous decay of the two-level system driven by the vacuum field. This probability is evaluated for a finite time interval. Using the standard argument to obtain the ...

International Nuclear Information System (INIS)

The canonical quantum theory of gravity-quantum geometrodynamics (QG)-is applied to the homogeneous Bianchi type IX cosmological model. As a result, a framework for the quantum theory of homogeneous cosmologies is developed. We show that the theory is internally consistent and prove that it possesses the correct classical limit (the theory of general relativity). To emphasize the special role that the constraints play in this new theory, we compare it to the traditional ADM square-root and Wheeler-DeWitt quantization schemes. We show that, unlike traditional approaches, QG leads to a well-defined Schroedinger equation for the wavefunction of the universe that is inherently coupled to the expectation value of the constraint equations. This coupling to the constraints is responsible for the appearance of a coherent spacetime picture. Thus, the physical meaning of the constraints of the theory is quite different from Dirac's ...

CERN Document Server

English abstract: In the "Intuitive Quantum Physics" course, we use graphical interpretations of mathematical equations and qualitative reasoning to develop and teach a simplified model of quantum physics. Our course contains three units: Wave physics, Development of a conceptual toolbox, and quantum physics. It also contains three key themes: wave-particle duality, the Schroedinger equation, and tunneling of quantum particles. Students learn most new material in lab-tutorials in which students work in small groups (3 to 3 people) on specially designed worksheets. Lecture reinforces the lab-tutorial content and focuses more on issues about the nature of science. Data show that students are able to learn some of the most difficult concepts in the course, and also that students learn to believe that there is a conceptually accessible structure to the physics in the course. German abstract: Im Kurs ...

Energy Technology Data Exchange (ETDEWEB)

Artificial neural network analysis is found to be far superior to multiple regression when applied to the evaluation of trap quality in the Northern Kuqa Depression, a gas-rich depression of Tarim Basin in western China. This is because this technique can correlate the complex and non-linear relationship between trap quality and related geological factors, whereas multiple regression can only describe a linear relationship. However, multiple regression can work as an auxiliary tool, as it is suited to high-speed calculations and can indicate the degree of dependence between the trap quality and its related geological factors which artificial neural network analysis cannot. For illustration, we have investigated 30 traps in the Northern Kuqa Depression. For each of the traps, the values of 14 selected geological factors were all known. While geologists were also able to assign individual trap quality values to 27 traps, they were less certain ...

CERN Document Server

Using some modification of the standard fermion technique we derive factorized formula for spin operator matrix elements (form-factors) between general eigenstates of the Hamiltonian of quantum Ising chain in a transverse field of finite length. The derivation is based on the approach recently used to derive factorized formula for Z_N-spin operator matrix elements between ground eigenstates of the Hamiltonian of the Z_N-symmetric superintegrable chiral Potts quantum chain. The obtained factorized formulas for the matrix elements of Ising chain coincide with the corresponding expressions obtained by the Separation of Variables Method.

Energy Technology Data Exchange (ETDEWEB)

We present a study of the interaction between Josephson junctions in circular superconducting rings and non-classical microwaves, treating both quantum mechanically. A Hamiltonian that describes both inductive and capacitive coupling between the two systems is derived within the external field approximation. Other Hamiltonians which go beyond the external field approximation, and describe explicitly the interaction of the quantum circuit that produces the non-classical microwaves with the Josephson junction circuit, are also presented. A comparison between current experiments which use classical electromagnetic fields and the proposed experiments that use non-classical microwaves, is made. (orig.) With 6 figs., 32 refs.

CERN Document Server

In the inflationary scenario of loop quantum cosmology (LQC) in the presence of inverse-volume corrections, we give analytic formulas for the power spectra of scalar and tensor perturbations convenient to confront with observations. Since inverse-volume corrections can provide strong contributions to the running spectral indices, inclusion of terms higher than the second-order runnings in the power spectra is crucially important. Using the recent data of cosmic microwave background (CMB) and other cosmological experiments, we place bounds on the quantum corrections for a quadratic inflaton potential.

CERN Document Server

It is proved the mathematical theorem, that the wave function describes the statistical ensemble of particles, but not a single particle. Supposition, that the wave function describes a single particle appears to be incompatible with formalism of quantum mechanics. One discusses the reasons, why this very simple statement has not been proved mathematically for many years. The reason lies in application of the trial and error methods for construction of the quantum mechanics. Application of this method as the main tool of investigation during eighty years generated "fitting mentality" of all microwold researchers.

CERN Document Server

An effective formalism for quantum constrained systems is presented which allows manageable derivations of solutions and observables, including a treatment of physical reality conditions without requiring full knowledge of the physical inner product. Instead of a state equation from a constraint operator, an infinite system of constraint functions on the quantum phase space of expectation values and moments of states is used. The examples of linear constraints as well as the free non-relativistic particle in parameterized form illustrate how standard problems of constrained systems can be dealt with in this framework.

Science.gov (United States)

We analyse the capacity of a simultaneous quantum secure direct communication scheme between the central party and other M parties via M+1-particle GHZ states and swapping quantum entanglement. It is shown that the encoding scheme should be secret if other M parties wants to transmit M+1 bit classical messages to the centre party secretly. However, when the encoding scheme is announced publicly, we prove that the capacity of the scheme in transmitting the secret messages is 2 bits, no matter how large M is.

British Library Electronic Table of Contents (United Kingdom)

There is a thermal range for the operation of neural circuits beyond which nervous system function is compromised. Locusta migratoria is native to the semiarid regions of the world and provides an excellent model for studying neural phenomena. In this organism previous exposure to sublethal high temperatures (heat shock, HS) can protect neuronal function against future hyperthermia but, unlike many organisms, the profound physiological adaptations are not accompanied by a robust increase of Hsp70 transcript or protein in the nervous system. We compared Hsp70 increase following HS in the tissues of isolated and gregarious locusts to investigate the effect of population density. We also localized Hsp70 in the metathoracic ganglion (MTG) of gregarious locusts to determine if HS affects Hsp70 ...

International Nuclear Information System (INIS)

In order to build the safety culture for nuclear power industry, it is important to evaluate the safety culture scientifically. Considering the traits of safety culture in the nuclear power industry, 24 safety culture assessment indexes are established from 4 aspects such as Safety consciousness, Safety attitude, Safety action and Safety actuality by using the SMART criteria. Safety culture star-class assessment criterion is presented and safety culture star-class assessment system is developed by using Visual Basic 6.0 and BP neural network. The system has a better generalization ability, and it can show exactly which phase the safety culture is in. Experimental results show that safety culture star-class assessment is practical and easy to perform. (authors)

Energy Technology Data Exchange (ETDEWEB)

This study has been carried out in the framework of a collaboration between the laboratory of processes automation (LAP, Caen (France)), and Air Com, a monitoring network for the prevention of atmospheric pollution in Basse-Normandie. It aims at obtaining a medium and long term forecast of the ozone level above the Caen city. The expected goal is to foresee the pollution peaks exceeding the warning thresholds, but the rareness of such events make them more difficult to predict. In order to solve this kind of problem, a neural modeling method combined with a noise injection technique has been implemented in order to obtain a sufficiently performing model over the whole domain of operation. (J.S.)

British Library Electronic Table of Contents (United Kingdom)

A marine propulsion system is a very complicated system composed of many mechanical components. As a result, the vibration signal of a gearbox in the system is strongly coupled with the vibration signatures of other components including a diesel engine and main shaft. It is therefore imperative to assess the coupling effect on diagnostic reliability in the process of gear fault diagnosis. For this reason, a fault detection and diagnosis method based on bispectrum analysis and artificial neural networks (ANNs) was proposed for the gearbox with consideration given to the impact of the other components in marine propulsion systems. To monitor the gear conditions, the bispectrum analysis was first employed to detect gear faults. The amplitude-frequency plots containing gear characteristic sign...

British Library Electronic Table of Contents (United Kingdom)

This article presents the micro-electro-mechanical systems (MEMS) microrobot which demonstrates locomotion controlled by hardware neural networks (HNN). The size of the microrobot fabricated by the MEMS technology is 4 ? 4 ? 3.5 mm. The frame of the robot is made of silicon wafer, and it is equipped with a rotary-type actuator, a link mechanism, and six legs. The rotary-type actuator generates rotational movement by applying an electrical current to artificial muscle wires. The locomotion of the microrobot is obtained by the rotation of the rotary-type actuator. As in a living organism, the HNN realized robot control without using any software programs, A/D converters, or additional driving circuits. A central pattern generator (CPG) model was implemented as an HNN system to emulate the lo...

British Library Electronic Table of Contents (United Kingdom)

Frozen boiled shrimp and dried shrimp are among the high-value fishery products of Thailand. During the production of these products boiling is one of the most important steps that affects significantly the product physicochemical properties, especially the quantity and quality of proteins, which in turn affect other apparent properties perceived by consumers. The protein changes are, however, difficult to evaluate comparing to other typical physical properties of shrimp. The objective of this study was therefore to develop an artificial neural network (ANN) model to predict the protein changes of shrimp in terms of protein loss and protein denaturation as a function of the boiling conditions, namely, concentration of salt solution and boiling time, as well as a rather easily determined ch...

Energy Technology Data Exchange (ETDEWEB)

The aim of this study is to develop the methodology which enables to identify the mechanical properties of element such as stress intensity factor by using the AE parameters. Considering the multivariate and nonlinear properties of AE parameters such as ringdown count, rise time, energy, event duration and peak amplitude from fatigue cracks of machine element the principal component regression(PCR) and artificial neural network(ANN) models for the estimation of stress intensity factor were developed and validated. The AE parameters were found to be very significant to estimate the stress intensity factor. Since the statistical values including correlation coefficients, standard mr of calibration, standard error of prediction and bias were stable, the PCR and ANN models for stress intensity factor were very robust. The performance of ANN model for unknown data of stress intensity factor was better than that of PCR model

British Library Electronic Table of Contents (United Kingdom)

Several challenges currently exist for rational design of functional tissue engineering constructs within the host, which include appropriate cellular integration, avoidance of bacterial infections, and low inflammatory stimulation. This work describes a novel class of biodegradable, amphiphilic polyanhydrides with many desirable protein-material and cell-material attributes capable of confronting these challenges. The biocompatible amphiphilic polymer films were shown to release laminin in a stable and controlled manner, promote neural cell adhesion and differentiation, and evade inflammatory responses of the immune system. Using high-throughput approaches, it was shown that polymer chemistry plays an integral role in controlling cell?film interactions, which suggests that these polyanhyd...

Energy Technology Data Exchange (ETDEWEB)

In the present scenario of market driven business, power supply has become more like a commodity. Reliable and quality power need to be ensured to meet customer requirements. In such a situation, it is extremely important that transmission line faults be identified accurately, reliably and in quick time. Advanced signal processing tools such as discrete wavelet transform (DWT) can be used very effectively for parameterisation and characterization of the fault signals. On the other hand, properly configured neural network (NN) can be utilized for classification of the faults based on the DWT signal. The present contribution uses electromagnetic transient program (EMTP) for modeling of a real transmission system and MATLAB for DWT and NN. Various types of faults have been simulated at different locations along the transmission line and an attempt has been made to correctly identify and locate the fault. (author)

Energy Technology Data Exchange (ETDEWEB)

A power system stabilizer based on GMV (Generalized Minimum Variance), one of the adaptive control techniques, is developed to enhance the dynamic performances of a power system using an Artificial Neural Network (ANN). The stabilizer consists of two parts. One part is Inverse Dynamics Neural Networks (IDNN), which is trained to identify the inverse dynamics of controlled plant and used as a one-step ahead controller, or inverse controller. The other part is Adaptive Reference Model (ARM), which prevents excessive controller output. The ARM produces the modified reference value by minimizing a cost function recursively on the assumption that the IDNN perfectly identifies the controlled plant. The IDNN is used in the minimization procedure to calculate the sensitivities. The proposed controller is simulated in a typical one-machine-infinite-bus power system to show its effectiveness to damp sustained low frequency oscillation. (author)

CERN Document Server

We investigate the relation between the symmetries of a quantum system and its topological quantum numbers, in a general C*-algebraic framework. We prove that, under suitable assumptions on the symmetry algebra, there exists a generalization of the Bloch-Floquet transform which induces a direct-integral decomposition of the algebra of observables. Such generalized transform selects uniquely the set of "continuous sections" in the direct integral, thus yielding a Hilbert bundle. The emerging geometric structure provides some topological invariants of the quantum system. Two running examples provide an Ariadne's thread through the paper. For the sake of completeness, we review two related theorems by von Neumann and Maurin and compare them with our result.

CERN Document Server

We analyze the driven resonantly coupled Jaynes-Cummings model in terms of a quasienergy approach by switching to a frame rotating with the external modulation frequency and by using the dressed atom picture. A quasienergy surface in phase space emerges whose level spacing is governed by a rescaled effective Planck constant. Moreover, the well-known multiphoton transitions can be reinterpreted as resonant tunneling transitions from the local maximum of the quasienergy surface. Most importantly, the driving defines a quasienergy well which is nonperturbative in nature. The quantum mechanical quasienergy state localized at its bottom is squeezed. In the Purcell limited regime, the potential well is metastable and the effective local temperature close to its minimum is uniquely determined by the squeezing factor. The activation occurs in this case via dressed spin flip transitions rather than via quantum activation as in other driven nonlinear ...

International Nuclear Information System (INIS)

This topical review provides an overview of quantum dot micropillars and their application in cavity quantum electrodynamics (cQED) experiments. The development of quantum dot micropillars is motivated by the study of fundamental cQED effects in solid state and their exploitation in novel light sources. In general, light-matter interaction occurs when the dipole of an emitter couples to the ambient light field. The corresponding coupling strength is strongly enhanced in the framework of cQED when the emitter is located inside a low mode volume microcavity providing three-dimensional photon confinement on a length scale of the photon wavelength. In addition, coherent coupling between light and matter, which is essential for applications in quantum information processing, can be achieved when dissipative losses, predominantly due to photon leakage out of the cavity, are strongly reduced. In this paper, we ...

International Nuclear Information System (INIS)

A quantum mechanical analysis of the guided light in integrated photonics waveguides is presented. The analysis is made starting from one-dimensional (1D) guided vector modes by taking into account the modal orthonormalization property on a cross section of an optical waveguide, the vector structure of the guided optical modes and the reversal-time symmetry in order to quantize the 1D vector modes and to derive the quantum momentum operator and the Heisenberg equations. The results provide a quantum-consistent formulation of the linear and nonlinear quantum light propagations as a function of forward and backward creation and annihilation operators in integrated photonics. As an illustration, an application to an integrated nonlinear directional coupler is given, that is, both the nonlinear momentum and the Heisenberg equations of the nonlinear coupler are derived.

International Nuclear Information System (INIS)

... Energy Agency, Quantum Beam Science Directorate, Sayo, Hyogo (Japan)

Science.gov (United States)

AlGaInP-based quantum-well laser diodes operating at wavelengths near 680 nm have been grown by all solid source molecular beam epitaxy (SSMBE). The lowest room temperature threshold current densities obtained from shallow rid structures were 300 A/cm{sup 2} and 330 A/cm{sup 2} for pulsed and continuous wave operation, respectively. The dependences of the differential quantum efficiency and threshold current density on the cavity length were also studied in this preliminary SSMBE work. The internal quantum efficiency of 87--89% and the internal losses of 7--10 cm{sup {minus}1} were obtained.

Science.gov (United States)

Excitonic transitions in metalorganic vapor phase epitaxially grown In[sub [ital x

CERN Document Server

The Arnowitt-Deser-Misner canonical formulation of general relativity is extended to the covariant brane-world theory in arbitrary dimensions. The exclusive probing of the extra dimensions makes a substantial difference, allowing for the construction of a non-constrained canonical theory. The quantum states of the brane-world geometry are defined by the Tomonaga-Schwinger equation, whose integrability conditions are determined by the classical perturbations of submanifolds contained in the Nash's differentiable embedding theorem. In principle, quantum brane-world theory can be tested by current experiments in astrophysics and by near future laboratory experiments at Tev energy. The implications to the black-hole information loss problem, to the accelerating cosmology, and to a quantum mathematical theory of four-sub manifolds are briefly commented.

CERN Document Server

The effective approach to quantum dynamics allows a reformulation of the Dirac quantization procedure for constrained systems in terms of an infinite-dimensional constrained system of classical type. For semiclassical approximations, the quantum constrained system can be truncated to finite size and solved by the reduced phase space or gauge-fixing methods. In particular, the classical feasibility of local internal times is directly generalized to quantum systems, overcoming the main difficulties associated with the general problem of time in the semiclassical realm. The key features of local internal times and the procedure of patching global solutions using overlapping intervals of local internal times are described and illustrated by two quantum mechanical examples. The choice of time is tantamount to a choice of gauge at the effective level and changing the clock is, therefore, equivalent to a gauge ...

CERN Document Server

The quantum nature of the electromagnetic field imposes a fundamental limit on the sensitivity of optical precision measurements such as spectroscopy, microscopy, and interferometry. The so-called quantum limit is set by the zero-point fluctuations of the electromagnetic field, which constrain the precision with which optical signals can be measured. In the world of precision measurement, laser-interferometric gravitational wave (GW) detectors are the most sensitive position meters ever operated, capable of measuring distance changes on the order of 10^-18 m RMS over kilometer separations caused by GWs from astronomical sources. The sensitivity of currently operational and future GW detectors is limited by quantum optical noise. Here we demonstrate a 44% improvement in displacement sensitivity of a prototype GW detector with suspended quasi-free mirrors at frequencies where the sensitivity is shot-noise-limited, by ...