Search results for "Gauss"

showing 10 items of 701 documents

Entanglement in continuous-variable systems: recent advances and current perspectives

2007

We review the theory of continuous-variable entanglement with special emphasis on foundational aspects, conceptual structures, and mathematical methods. Much attention is devoted to the discussion of separability criteria and entanglement properties of Gaussian states, for their great practical relevance in applications to quantum optics and quantum information, as well as for the very clean framework that they allow for the study of the structure of nonlocal correlations. We give a self-contained introduction to phase-space and symplectic methods in the study of Gaussian states of infinite-dimensional bosonic systems. We review the most important results on the separability and distillabil…

High Energy Physics - TheoryStatistics and ProbabilityINFORMATIONField (physics)Computer scienceGaussianStructure (category theory)FOS: Physical sciencesGeneral Physics and AstronomyQuantum entanglementMultipartite entanglementUnitary statesymbols.namesakeRADIATION-FIELDSEPARABILITY CRITERIONStatistical physicsQuantum informationNORMAL FORMSCondensed Matter - Statistical MechanicsMathematical PhysicsQuantum opticsQuantum PhysicsStatistical Mechanics (cond-mat.stat-mech)ERROR-CORRECTIONENTROPYStatistical and Nonlinear PhysicsQUANTUM TELEPORTATION NETWORK MIXED-STATE ENTANGLEMENT GAUSSIAN STATES SEPARABILITY CRITERION ERROR-CORRECTION RADIATION-FIELD NORMAL FORMS INEQUALITIES INFORMATION ENTROPYMathematical Physics (math-ph)Quantum PhysicsMIXED-STATE ENTANGLEMENTGAUSSIAN STATESHigh Energy Physics - Theory (hep-th)QUANTUM TELEPORTATION NETWORKModeling and SimulationINEQUALITIESsymbolsQuantum Physics (quant-ph)Physics - OpticsOptics (physics.optics)
researchProduct

Foreword: Prof. Gauss Festschrift

2020

As guest editors, we are excited to present the Molecular Physics Festschrift in honour of Jurgen Gauss, professor of theoretical chemistry at the Johannes Gutenberg-Universitat Mainz, Germany, on ...

HonourTheoretical physicsmedia_common.quotation_subjectPhilosophyGaussBiophysicsPhysical and Theoretical ChemistryCondensed Matter PhysicsMolecular Biologymedia_commonMolecular Physics
researchProduct

Passive millimeter wave image classification with large scale Gaussian processes

2017

Passive Millimeter Wave Images (PMMWIs) are being increasingly used to identify and localize objects concealed under clothing. Taking into account the quality of these images and the unknown position, shape, and size of the hidden objects, large data sets are required to build successful classification/detection systems. Kernel methods, in particular Gaussian Processes (GPs), are sound, flexible, and popular techniques to address supervised learning problems. Unfortunately, their computational cost is known to be prohibitive for large scale applications. In this work, we present a novel approach to PMMWI classification based on the use of Gaussian Processes for large data sets. The proposed…

HyperparameterContextual image classificationbusiness.industryComputer scienceSupervised learning0211 other engineering and technologiesInferencePattern recognition02 engineering and technologysymbols.namesakeBayes' theoremKernel (linear algebra)Kernel methodKernel (statistics)0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processingArtificial intelligencebusinessGaussian process021101 geological & geomatics engineering2017 IEEE International Conference on Image Processing (ICIP)
researchProduct

Biophysical parameter estimation with adaptive Gaussian Processes

2009

We evaluate Gaussian Processes (GPs) for the estimation of biophysical parameters from acquired multispectral data. The standard GP formulation is used, and all hyperparameters (kernel parameters and noise variance) are optimized by maximizing the marginal likelihood. This gives rise to a fully-adaptive GP to data characteristics, both in terms of signal and noise properties. The good numerical results in the estimation of oceanic chlorophyll concentration and leaf membrane state confirm GPs as adequate, alternative non-parametric methods for biophysical parameter estimation. GPs are also analyzed by scrutinizing the predictive variance, the estimated noise variance, and the relevance of ea…

Hyperparameterbusiness.industryEstimation theoryNoise (signal processing)Pattern recognitionVariance (accounting)Marginal likelihoodsymbols.namesakeKernel methodKernel (statistics)symbolsArtificial intelligencebusinessGaussian processAlgorithmMathematics2009 IEEE International Geoscience and Remote Sensing Symposium
researchProduct

Statistical Properties of Double Hoyt Fading With Applications to the Performance Analysis of Wireless Communication Systems

2018

In this paper, we investigate the statistical properties of double Hoyt fading channels, where the overall received signal is determined by the product of two statistically independent but not necessarily identically distributed single Hoyt processes. Finite-range integral expressions are first derived for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades of the envelope fading process. A closed-form approximate solution is also deduced for the LCR by making use of the Laplace approximation theorem. Applying the derived PDF of the double Hoyt channel, we then provide analytical expressions for the average…

Independent and identically distributed random variablesGeneral Computer ScienceGaussianProbability density function02 engineering and technologyDouble Hoyt fading channel modelsymbols.namesake0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceFadingGaussian processMathematicsComputer Science::Information TheoryCumulative distribution function020208 electrical & electronic engineeringMathematical analysisGeneral Engineering020206 networking & telecommunicationsvehicular-to-vehicular (V2V) channelsLaplace's methodprobability density function (PDF)symbolsaverage duration of fades (ADF)cumulative distribution function (CDF)lcsh:Electrical engineering. Electronics. Nuclear engineeringlevel-crossing rate (LCR)lcsh:TK1-9971Quadrature amplitude modulationIEEE Access
researchProduct

Prospects for constraining the shape of non-Gaussianity with the scale-dependent bias

2012

We consider whether the non-Gaussian scale-dependent halo bias can be used not only to constrain the local form of non-Gaussianity but also to distinguish among different shapes. In particular, we ask whether it can constrain the behavior of the primordial three-point function in the squeezed limit where one of the momenta is much smaller than the other two. This is potentially interesting since the observation of a three-point function with a squeezed limit that does not go like the local nor equilateral templates would be a signal of non-trivial dynamics during inflation. To this end we use the quasi-single field inflation model of Chen and Wang as a representative two-parameter model, wh…

Inflation (cosmology)PhysicsAstrofísicaCosmology and Nongalactic Astrophysics (astro-ph.CO)Cosmologia010308 nuclear & particles physicsFísicaFOS: Physical sciencesAstronomy and AstrophysicsFunction (mathematics)Astrophysics::Cosmology and Extragalactic AstrophysicsAstrophysics01 natural sciencesCosmologyNon-Gaussianity0103 physical sciencesHalo effectDark energyRange (statistics)Limit (mathematics)Statistical physics010303 astronomy & astrophysicsBispectrumAstrophysics - Cosmology and Nongalactic Astrophysics
researchProduct

Probabilistic quantum clustering

2020

Abstract Quantum Clustering is a powerful method to detect clusters with complex shapes. However, it is very sensitive to a length parameter that controls the shape of the Gaussian kernel associated with a wave function, which is employed in the Schrodinger equation with the role of a density estimator. In addition, linking data points into clusters requires local estimates of covariance which requires further parameters. This paper proposes a Bayesian framework that provides an objective measure of goodness-of-fit to the data, to optimise the adjustable parameters. This also quantifies the probabilities of cluster membership, thus partitioning the data into a specific number of clusters, w…

Information Systems and ManagementJaccard indexComputer scienceProbabilistic logicEstimatorProbability density function02 engineering and technologyFunction (mathematics)CovarianceMeasure (mathematics)Management Information Systemssymbols.namesakeArtificial Intelligence020204 information systems0202 electrical engineering electronic engineering information engineeringGaussian functionsymbolsCluster (physics)020201 artificial intelligence & image processingStatistical physicsQASoftwareQuantum clusteringKnowledge-Based Systems
researchProduct

Information Decomposition in Multivariate Systems: Definitions, Implementation and Application to Cardiovascular Networks

2016

The continuously growing framework of information dynamics encompasses a set of tools, rooted in information theory and statistical physics, which allow to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of complex networks. Building on the most recent developments in this field, this work designs a complete approach to dissect the information carried by the target of a network of multiple interacting systems into the new information produced by the system, the information stored in the system, and the information transferred to it from the other systems; information storage and transfer are then further decomposed into amou…

Information transferDynamical systems theoryComputer scienceGeneral Physics and Astronomylcsh:AstrophysicsInformation theorycomputer.software_genreMachine learning01 natural sciencesEntropy - Cardiorespiratory interactions - Dynamical systems -cardiovascular interactions03 medical and health sciencessymbols.namesake0302 clinical medicinelcsh:QB460-4660103 physical sciencesinformation transferEntropy (information theory)lcsh:Science010306 general physicsGaussian processautoregressive processesmultivariate time series analysisbusiness.industryautonomic nervous systemredundancy and synergycardiorespiratory interactionsdynamical systemsComplex networkNetwork dynamicslcsh:QC1-999autonomic nervous system; autoregressive processes; cardiorespiratory interactions; cardiovascular interactions; Granger causality; dynamical systems; information dynamics; information transfer; redundancy and synergy; multivariate time series analysisAutoregressive modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalitysymbolslcsh:QArtificial intelligenceData mininginformation dynamicsbusinesscomputerlcsh:Physics030217 neurology & neurosurgeryEntropy; Volume 19; Issue 1; Pages: 5
researchProduct

Empathes: A general code for nudged elastic band transition states search

2022

Abstract An easy and flexible interface, Empathes (Extensible Minimum PATH EStimator), that allows to perform Nudged Elastic Band calculation for the determination of transition states is presented. The code is designed to be easily modified, in order to be associated with the user's preferred calculation software, even with those which implement composite approaches. In particular, the interfaces to Gaussian and Siesta programs are discussed in details, being the former only used for testing purpose, while the latter can be productively employed for transition states search with that commonly used density functional theory software for periodic calculations. Program summary Program Title: …

Interface (Java)business.industryComputer scienceFortranGaussianNEBGeneral Physics and AstronomySiestaComputational sciencesymbols.namesakeSoftwareHardware and ArchitectureChemical reactionsPath (graph theory)symbolsSIESTA (computer program)businessRealization (systems)Reactive systemcomputercomputer.programming_languageComputer Physics Communications
researchProduct

Theoretical rotational constants of MeCnN species

1990

Abstract By means of SCF HF “ab initio” calculations with STO-3G and 6-31G basis sets, the geometric parameters of methylcyanopolyynes (MeCnN n=3, 5, 7 and 9) have been obtained. B0=0.3748 GHz for MeC7N and B0=0.2708 GHz for MeC9N, with a STO-3G basis set, were obtained. Both species, unstable in the laboratory, are still undetected in the interstellar medium, although their existence is very probable.

Interstellar mediumchemistry.chemical_compoundCondensed matter physicsBasis (linear algebra)NitrileChemistryGaussian orbitalAb initioGeneral Physics and AstronomyRotational spectroscopyPhysical and Theoretical ChemistryMolecular physicsBasis setChemical Physics Letters
researchProduct