Search results for "FACTORIZATION"

showing 10 items of 221 documents

Theory of ground state factorization in quantum cooperative systems.

2008

We introduce a general analytic approach to the study of factorization points and factorized ground states in quantum cooperative systems. The method allows to determine rigorously existence, location, and exact form of separable ground states in a large variety of, generally non-exactly solvable, spin models belonging to different universality classes. The theory applies to translationally invariant systems, irrespective of spatial dimensionality, and for spin-spin interactions of arbitrary range.

High Energy Physics - TheoryQuantum phase transitionGeneral Physics and AstronomyFOS: Physical sciencesFactorizationfactorizationQuantum mechanicsStatistical physicsSOLVABLE MODELVALIDITYENTANGLEMENTQuantumMathematical PhysicsMathematicsQuantum PhysicsMathematical Physics (math-ph)Invariant (physics)BODY APPROXIMATION METHODSUniversality (dynamical systems)Condensed Matter - Other Condensed MatterClosed and exact differential formsHigh Energy Physics - Theory (hep-th)SPIN CHAINGround stateQuantum Physics (quant-ph)Curse of dimensionalityOther Condensed Matter (cond-mat.other)Physical review letters
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Forward dijets in proton-nucleus collisions at next-to-leading order: the real corrections

2021

Using the CGC effective theory together with the hybrid factorisation, we study forward dijet production in proton-nucleus collisions beyond leading order. In this paper, we compute the "real" next-to-leading order (NLO) corrections, i.e. the radiative corrections associated with a three-parton final state, out of which only two are being measured. To that aim, we start by revisiting our previous results for the three-parton cross-section presented in our previous paper. After some reshuffling of terms, we deduce new expressions for these results, which not only look considerably simpler, but are also physically more transparent. We also correct several errors in this process. The real NLO …

High Energy Physics - Theorydijet: productionNuclear and High Energy PhysicsParticle physicsNuclear TheoryProton[PHYS.NUCL]Physics [physics]/Nuclear Theory [nucl-th]splittingFOS: Physical sciencescollinearParton01 natural sciencesColor-glass condensateNuclear Theory (nucl-th)DGLAP equationHigh Energy Physics - Phenomenology (hep-ph)FactorizationfactorizationNLO Computations0103 physical sciencesRadiative transferEffective field theoryradiative correctionlcsh:Nuclear and particle physics. Atomic energy. Radioactivitypartonheavy ion phenomenology010306 general physicsp nucleus: scatteringPhysicsNLO computationshybrid010308 nuclear & particles physics[PHYS.HTHE]Physics [physics]/High Energy Physics - Theory [hep-th]higher-order: 1Heavy Ion PhenomenologyGluonHigh Energy Physics - PhenomenologyDGLAPHigh Energy Physics - Theory (hep-th)kinematics[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph]color glass condensatelcsh:QC770-798
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Multi-boson block factorization of fermions

2017

The numerical computations of many quantities of theoretical and phenomenological interest are plagued by statistical errors which increase exponentially with the distance of the sources in the relevant correlators. Notable examples are baryon masses and matrix elements, the hadronic vacuum polarization and the light-by-light scattering contributions to the muon g-2, and the form factors of semileptonic B decays. Reliable and precise determinations of these quantities are very difficult if not impractical with state-of-the-art standard Monte Carlo integration schemes. I will review a recent proposal for factorizing the fermion determinant in lattice QCD that leads to a local action in the g…

High Energy Physics::Latticeaction: local01 natural sciencesHigh Energy Physics - Phenomenology (hep-ph)Vacuum polarizationcorrelation functionQuantum Chromodynamics Lattice gauge theory Computational PhysicsMonte CarloBosonPhysicsform factorPhysicsHigh Energy Physics - Lattice (hep-lat)lattice field theoryPropagatorpropagator [quark]hep-phParticle Physics - Latticestatistical [error]Lattice QCDFIS/02 - FISICA TEORICA MODELLI E METODI MATEMATICIHigh Energy Physics - Phenomenologyerror: statisticalquark: factorizationquark: propagatorMonte Carlo integrationQuarkParticle physicsQC1-999fermion: determinantdeterminant [fermion]FOS: Physical scienceshep-latbaryon: massHigh Energy Physics - LatticeFactorization0103 physical sciencesmagnetic moment [muon]hadronic [vacuum polarization]010306 general physicsnumerical calculationsParticle Physics - Phenomenologymuon: magnetic moment010308 nuclear & particles physicsvacuum polarization: hadronicHigh Energy Physics::Phenomenologyphoton photon: scatteringB: decaylocal [action]Fermiondecay [B]mass [baryon]scattering [photon photon]gauge field theoryHigh Energy Physics::Experimentfactorization [quark]
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Searches for B0 decays to combinations of charmless isoscalar mesons

2004

We search for B meson decays into two-body combinations of eta, eta', omega, and phi mesons from 89 million B B-bar pairs collected with the BaBar detector at the PEP-II asymmetric-energy e+e- collider at SLAC. We find the branching fraction BF(B0 -> eta omega) = (4.0^{+1.3}_{-1.2} +- 0.4) x 10^-6 with a significance of 4.3 sigma. For all the other decay modes we set the following 90% confidence level upper limits on the branching fractions, in units of 10^-6 : BF(B0 -> eta eta)<2.8, BF(B0 -> eta eta')<4.6, BF(B0 -> eta' eta')<10, BF(B0 -> eta'omega)<2.8, BF(B0 -> eta phi)<1.0, BF(B0 -> eta' phi)<4.5, BF(B0 -> phi phi)<1.5.

IsoscalarElectron–positron annihilationBABARGeneral Physics and AstronomyQCD FACTORIZATION01 natural sciencesOmega13.25.Hw 11.30.Er 12.15.HhHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)Mathematical modelProbability density function[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]PEP2B mesonNuclear ExperimentQCD FACTORIZATION; STANDARD MODEL; BABAR; SLACPhysicsQuantum chromodynamicsSigmaHamiltonianMonte Carlo methodSensitivity analysiPARTICLE PHYSICSBranching fractionSLACParticle physicsMesonSTANDARD MODELQCD FACTORIZATION STANDARD MODELFOS: Physical sciencesLikelihood distributionPARTICLE PHYSICS; PEP2; BABARSolenoidHigh energy physicNuclear physicsPhysics and Astronomy (all)ElectromagnetismElectromagnetic calorimeterPseudoscalar meson0103 physical sciencesPerturbation technique010306 general physicsCalorimeterError analysi010308 nuclear & particles physicsBranching fractionHEPMagnetic fieldHigh Energy Physics::Experiment
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BENEFITS OF MULTI-DOMAIN FEATURE OF MISMATCH NEGATIVITY EXTRACTED BY NON-NEGATIVE TENSOR FACTORIZATION FROM EEG COLLECTED BY LOW-DENSITY ARRAY

2012

Through exploiting temporal, spectral, time-frequency representations, and spatial properties of mismatch negativity (MMN) simultaneously, this study extracts a multi-domain feature of MMN mainly using non-negative tensor factorization. In our experiment, the peak amplitude of MMN between children with reading disability and children with attention deficit was not significantly different, whereas the new feature of MMN significantly discriminated the two groups of children. This is because the feature was derived from multi-domain information with significant reduction of the heterogeneous effect of datasets.

MaleReading disabilityAdolescentComputer Networks and CommunicationsSpeech recognitionMismatch negativityContingent Negative VariationElectroencephalographybehavioral disciplines and activitiesDyslexiaReduction (complexity)Event-related potentialmedicineHumansChildMathematicsModels StatisticalTensor factorizationmedicine.diagnostic_testbusiness.industryElectroencephalographyPattern recognitionGeneral MedicineBrain WavesAmplitudeAcoustic StimulationAttention Deficit Disorder with HyperactivityFeature (computer vision)Case-Control StudiesAuditory PerceptionEvoked Potentials AuditoryFemaleArtificial intelligencebusinesspsychological phenomena and processesInternational Journal of Neural Systems
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Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm

2013

International audience; We present in this paper the decomposition of human skin absorption spectra with a Non-negative Matrix Factorization method. In doing so, we are able to quantify the relative proportion of the main chromophores present in the epidermis and the dermis. We present experimental results showing that we obtain a good estimate of melanin and hemoglobin concentrations. Our approach has been validated by analyzing the human skin absorption spectra in areas of healthy skin and areas affected by melasma on eight patients.

Materials science[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingAbsorption spectroscopyMelasmaHealth InformaticsHuman skin02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesNon-negative Matrix FactorizationNon-negative matrix factorizationMatrix decomposition010309 opticsSpectral reconstructionOpticsDermis[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingChromophores quantificationOptical reflectance[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingintegumentary systembusiness.industrymedicine.diseasemedicine.anatomical_structureSignal Processing020201 artificial intelligence & image processingEpidermisSkin optical reflectance mapsbusinessBiological system[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A choice of bilevel linear programming solving parameters: factoraggregation approach

2013

Our paper deals with the problem of choosing correct parameters for the bilevel linear program- ming solving algorithm proposed by M. Sakawa and I. Nishizaki. We suggest an approach based on fac- toraggregation, which is a specially designed general aggregation operator. The idea of factoraggregation arises from factorization by the equivalence relation generated by the upper level objective function. We prove several important properties of the factorag- gregation result regarding the analysis of param- eters in order to find an optimal solution for the problem. We illustrate the proposed method with some numerical and graphical examples, in particu- lar we consider a modification of the m…

Mathematical optimizationLinear programmingComputer scienceMonotonic functionFuzzy logicMultiobjective linear programming problemOperator (computer programming)Production planningBilevel linear programming problemFactorizationEquivalence relationBoundary value problem:MATHEMATICS::Applied mathematics [Research Subject Categories]General aggregation operator
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Detecting Inclusions in Electrical Impedance Tomography Without Reference Measurements

2009

We develop a new variant of the factorization method that can be used to detect inclusions in electrical impedance tomography from either absolute current-to-voltage measurements at a single, nonzero frequency or from frequency-difference measurements. This eliminates the need for numerically simulated reference measurements at an inclusion-free body and thus greatly improves the method's robustness against forward modeling errors, e.g., in the assumed body's shape.

Mathematical optimizationRobustness (computer science)Applied MathematicsFactorization methodNew variantInverse problemAlgorithmElectrical impedance tomographyMathematicsSIAM Journal on Applied Mathematics
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Analysis of human skin hyper-spectral images by non-negative matrix factorization

2011

International audience; This article presents the use of Non-negative Matrix Factorization, a blind source separation algorithm, for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The evaluated spectra come from a Hyper-Spectral Image, which is the result of the processing of a Multi-Spectral Image by a neural network-based algorithm. The implemented source separation algorithm is based on a multiplicative coeffi cient upload. The goal is to represent a given spectrum as the weighted sum of two spectral components. The resulting weighted coefficients are used to quantify melanin and hemoglobin content in the given spectra. Results present a …

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingAbsorption spectroscopy[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMelasmaComputer sciencePhysics::Medical PhysicsPopulation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesNon-negative Matrix FactorizationSpectral line030218 nuclear medicine & medical imagingNon-negative matrix factorizationMatrix decomposition010309 opticsBlind source separation algorithms03 medical and health sciences0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesSource separationmedicineMulti/Hyper-Spectral imagingeducation[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingeducation.field_of_studyArtificial neural networkbusiness.industrySpectrum (functional analysis)Pattern recognitionmedicine.diseaseArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processinghuman skin absorbance spectrum
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Mass transportation on sub-Riemannian structures of rank two in dimension four

2017

International audience; This paper is concerned with the study of the Monge optimal transport problem in sub-Riemannian manifolds where the cost is given by the square of the sub-Riemannian distance. Our aim is to extend previous results on existence and uniqueness of optimal transport maps to cases of sub-Riemannian structures which admit many singular minimizing geodesics. We treat here the case of sub-Riemannian structures of rank two in dimension four.

Mathematics - Differential Geometry[ MATH ] Mathematics [math]Rank (linear algebra)Geodesicpolar factorization[MATH] Mathematics [math]01 natural sciencesSquare (algebra)CombinatoricsDimension (vector space)0103 physical sciencesFOS: MathematicsUniqueness0101 mathematicsMass transportation[MATH]Mathematics [math]Mathematical PhysicsComputingMilieux_MISCELLANEOUSMathematicsApplied Mathematics010102 general mathematicsSub-Riemannian geometryDifferential Geometry (math.DG)[MATH.MATH-DG]Mathematics [math]/Differential Geometry [math.DG]010307 mathematical physicsMathematics::Differential GeometryAnalysisOptimal transport problem
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