Search results for " Mathematica"

showing 10 items of 689 documents

Nilpotence of orbits under monodromy and the length of Melnikov functions

2021

Abstract Let F ∈ ℂ [ x , y ] be a polynomial, γ ( z ) ∈ π 1 ( F − 1 ( z ) ) a non-trivial cycle in a generic fiber of F and let ω be a polynomial 1-form, thus defining a polynomial deformation d F + e ω = 0 of the integrable foliation given by F . We study different invariants: the orbit depth k , the nilpotence class n , the derivative length d associated with the couple ( F , γ ) . These invariants bind the length l of the first nonzero Melnikov function of the deformation d F + e ω along γ . We analyze the variation of the aforementioned invariants in a simple but informative example, in which the polynomial F is defined by a product of four lines. We study as well the relation of this b…

PhysicsPure mathematicsSequencePolynomialConjectureMelnikov functionAbelian integrals010102 general mathematicsStatistical and Nonlinear PhysicsIterated integralsCondensed Matter Physics01 natural sciencesNilpotence classFoliationDisplacement functionLimit cyclesMonodromySimple (abstract algebra)[MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph]Product (mathematics)0103 physical sciences010307 mathematical physics0101 mathematicsOrbit (control theory)ComputingMilieux_MISCELLANEOUS
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QCD condensates from tau-decay data: A functional approach

2004

We study a functional method to extract the V − A condensate of dimension 6 from a comparison of τ -decay data with the asymptotic space-like QCD prediction. Our result is in agreement within errors with that from conventional analyses based on finite energy sum rules.

PhysicsQuantum chromodynamicsNuclear and High Energy PhysicsFunctional approachFOS: Physical sciencesPerturbation (Mathematics)Mathematical analysisRenormalization (Physics)High Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Dimension (vector space)Quantum mechanics[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph]Quantum chromodynamics -- Mathematical modelsSum rule in quantum mechanicsEnergy (signal processing)
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A calorimeter for the precise determination of the activity of the 144Ce-144Pr anti-neutrino source in the SOX experiment

2018

We describe the design and the performance of a high precision thermal calorimeter, whose purpose was the measurement of the total activity of the 144Ce-144Pr anti-neutrino source of the SOX (Short distance neutrino Oscillation with BoreXino) experiment. SOX aimed at the search for eV-scale sterile neutrinos by means of the Borexino detector at the Laboratori Nazionali del Gran Sasso in Italy and of a very powerful artificial anti-neutrino source located at 8.51 m from the detector center. In order to obtain the required sensitivity, the activity of the source (approximately 150 kCi) had to be known at 1% precision. In this work we report the design of the experimental apparatus and the res…

PhysicsRadiation monitoringPhysics::Instrumentation and Detectors010308 nuclear & particles physicsDetector01 natural sciencesParticle detectorCalorimeterNuclear physicsCalorimetersNeutrino detectorMockup0103 physical sciencesHigh Energy Physics::ExperimentNeutrinoCalorimeters; Radiation monitoring; Instrumentation; Mathematical Physics010306 general physicsNeutrino oscillationInstrumentationMathematical PhysicsBorexinoJournal of Instrumentation
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Scattering on Riemannian Symmetric Spaces and Huygens Principle

2018

International audience; The famous paper by L. D. Faddeev and B. S. Pavlov (1972) on automorphic wave equation explored a highly romantic link between Scattering Theory (in the sense of Lax and Phillips) and Riemann hypothesis. An attempt to generalize this approach to general semisimple Lie groups leads to an interesting evolution system with multidimensional time explored by the author in 1976. In the present paper, we compare this system with a simpler one defined for zero curvature symmetric spaces and show that the Huygens principle for this system in the curved space holds if and only if it holds in the zero curvature limit.

PhysicsScattering010102 general mathematicsStatistical and Nonlinear Physics16. Peace & justiceWave equation01 natural sciencesHuygens–Fresnel principlesymbols.namesakeRiemann hypothesis[MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph]0103 physical sciencessymbols010307 mathematical physicsScattering theory0101 mathematicsLink (knot theory)Mathematical PhysicsMathematical physics
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Three-state quantum systems: A procedure for the solution

1989

An iterative method to obtain a solution of the differential equation $$i\dot a = \hat H(t)a$$ , with Ĥ a 3×3 Hermitian matrix anda the unknown vector, is proposed. The procedure is particularly suitable for computer implementation and, as an example, has been applied to find the excitation probability of a three-level atom after the synchronous passage of two laser pulses each almost resonant with a pair of atomic levels.

PhysicsSettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciIterative methodDifferential equationGeneral Physics and AstronomyAtom (order theory)State (functional analysis)LaserHermitian matrixlaw.inventionlawQuantum mechanicsGeneral mathematical and computational developmentQuantumExcitationIl Nuovo Cimento D
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Apparent remote synchronization of amplitudes: A demodulation and interference effect

2018

A form of "remote synchronization" was recently described, wherein amplitude fluctuations across a ring of non-identical, non-linear electronic oscillators become entrained into spatially-structured patterns. According to linear models and mutual information, synchronization and causality dip at a certain distance, then recover before eventually fading. Here, the underlying mechanism is finally elucidated through novel experiments and simulations. The system non-linearity is found to have a dual role: it supports chaotic dynamics, and it enables the energy exchange between the lower and higher sidebands of a predominant frequency. This frequency acts as carrier signal in an arrangement rese…

PhysicsSidebandApplied MathematicsStatistical and Nonlinear Physics; Mathematical Physics; Physics and Astronomy (all); Applied MathematicsFOS: Physical sciencesGeneral Physics and AstronomyStatistical and Nonlinear PhysicsNonlinear Sciences - Chaotic DynamicsTopologyInterference (wave propagation)01 natural sciences010305 fluids & plasmasAmplitude modulationPhysics and Astronomy (all)Amplitude0103 physical sciencesBasebandMathematical PhysicDemodulationFadingTransfer entropyChaotic Dynamics (nlin.CD)010306 general physicsMathematical PhysicsStatistical and Nonlinear PhysicChaos: An Interdisciplinary Journal of Nonlinear Science
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Computing absolute free energies of disordered structures by molecular simulation

2009

We present a Monte Carlo simulation technique by which the free energy of disordered systems can be computed directly. It is based on thermodynamic integration. The central idea is to construct an analytically solvable reference system from a configuration which is representative for the state of interest. The method can be applied to lattice models (e.g., the Ising model) as well as off-lattice molecular models. We focus mainly on the more challenging off-lattice case. We propose a Monte Carlo algorithm, by which the thermodynamic integration path can be sampled efficiently. At the examples of the hard sphere liquid and a hard disk solid with a defect, we discuss several properties of the …

PhysicsStatistical Mechanics (cond-mat.stat-mech)Monte Carlo method: Physics [G04] [Physical chemical mathematical & earth Sciences]General Physics and AstronomyThermodynamic integrationFOS: Physical sciencesMolecular simulationCondensed Matter - Soft Condensed Matter: Physique [G04] [Physique chimie mathématiques & sciences de la terre]Lattice (order)Soft Condensed Matter (cond-mat.soft)Free energiesIsing modelStatistical physicsPhysical and Theoretical ChemistryCondensed Matter - Statistical MechanicsMonte Carlo algorithm
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Characterisation and mitigation of beam-induced backgrounds observed in the ATLAS detector during the 2011 proton-proton run

2013

This paper presents a summary of beam-induced backgrounds observed in the ATLAS detector and discusses methods to tag and remove background contaminated events in data. Triggerrate based monitoring of beam-related backgrounds is presented. The correlations of backgrounds with machine conditions, such as residual pressure in the beam-pipe, are discussed. Results from dedicated beam-background simulations are shown, and their qualitative agreement with data is evaluated. Data taken during the passage of unpaired, i.e. non-colliding, proton bunches is used to obtain background-enriched data samples. These are used to identify characteristic features of beam-induced backgrounds, which then are …

Physics::Instrumentation and DetectorsAccelerator modelling and simulations; multi-particle dynamics; Analysis and statistical methods; Pattern recognition cluster finding calibration and fitting methods; Performance of High Energy Physics Detectors; single-particle dynamicsPROTON BEAMSMonte Carlo methodsingle-particle dynamics01 natural sciencesaccelerator modelling and simulations (multi-particle dynamics; single-particle dynamics)High Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)MUON DETECTORcluster findingPIXEL DETECTORSNaturvetenskap[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]GeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)InstrumentationQCMathematical PhysicsPhysicsLarge Hadron ColliderPattern recognition cluster finding calibration and fitting methodsAccelerator modelling and simulations (multi-particle dynamics; single-particle dynamics)Settore FIS/01 - Fisica SperimentaleObservableATLAScalibration and fitting methodsAccelerator modelling and simulationsCalorimetermedicine.anatomical_structureBunchesAccelerator Modelling and Simulations (Multi-Particle Dynamics Single-Particle Dynamics)Analysis and statistical methodsLHCmulti-particle dynamicsNatural SciencesParticle Physics - ExperimentParticle physicsCiências Naturais::Ciências Físicas530 PhysicsInstrumentationCALORIMETERS:Ciências Físicas [Ciências Naturais]FOS: Physical sciencesddc:500.2530Nuclear physicssingle-particle dynamics)Atlas (anatomy)Pattern recognition0103 physical sciencesmedicineAccelerator modelling and simulations (multi-particle dynamics single-particle dynamics)High Energy Physicspattern recognition; cluster finding; calibration and fitting methods; single-particle dynamics); analysis and statistical methods; accelerator modelling and simulations (multi-particle dynamics; performance of high energy physics detectorsddc:610010306 general physicsCalibration and fitting methodsScience & Technology010308 nuclear & particles physicsCluster findingFísicaAccelerator modelling and simulations (multi-particle dynamicsAccelerator modelling and simulations (multi-particle dynamics; Analysis and statistical methods; Pattern recognition cluster finding calibration and fitting methods; Performance of High Energy Physics Detectors; single-particle dynamics); Instrumentation; Mathematical PhysicsExperimental High Energy PhysicsPattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors; Accelerator modelling and simulations (multi-particle dynamics; single-particle dynamics); Analysis and statistical methodsPhysics::Accelerator PhysicsPerformance of High Energy Physics DetectorsEvent (particle physics)
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A neural network clustering algorithm for the ATLAS silicon pixel detector

2014

A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. …

Physics::Instrumentation and DetectorsCiencias FísicasMonte Carlo methodHigh Energy Physics - Experiment//purl.org/becyt/ford/1 [https]High Energy Physics - Experiment (hep-ex)jetParticle tracking detectors[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]scattering [p p]Statistical physicscluster [track data analysis]Particle tracking detectors (solid-state detectors)InstrumentationQCMathematical PhysicsPhysicsArtificial neural networkAtlas (topology)Detectordetectors)Monte Carlo [numerical calculations]ATLASperformance [neural network]CERN LHC CollParticle tracking detectors (Solid-state detectors)Feature (computer vision)Physical SciencesParticle tracking detectors (Solid-stateParticle tracking detectors; Particle tracking detectors (Solid-state detectors)ComputingMethodologies_DOCUMENTANDTEXTPROCESSINGLHCConnected-component labelingAlgorithmNeural networksCIENCIAS NATURALES Y EXACTASParticle Physics - ExperimentInterpolationCiências Naturais::Ciências Físicas530 Physicssplitting:Ciências Físicas [Ciências Naturais]FOS: Physical sciencesParticle tracking detectors; Particle tracking detectors (solid-state detectors); Instrumentation; Mathematical Physics530FysikHigh Energy Physicsddc:610Cluster analysispixel [semiconductor detector]Science & TechnologyFísica//purl.org/becyt/ford/1.3 [https]High Energy Physics - Experiment; High Energy Physics - ExperimentParticle tracking detectorcluster [charged particle]AstronomíaParticle tracking detectors; Particle tracking detectors (Solid-state; detectors)Experimental High Energy Physicsimpact parameter [resolution]
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Pointwise Inequalities for Sobolev Functions on Outward Cuspidal Domains

2019

Abstract We show that the 1st-order Sobolev spaces $W^{1,p}(\Omega _\psi ),$$1<p\leq \infty ,$ on cuspidal symmetric domains $\Omega _\psi $ can be characterized via pointwise inequalities. In particular, they coincide with the Hajłasz–Sobolev spaces $M^{1,p}(\Omega _\psi )$.

PointwisePure mathematicsMathematics::Functional AnalysisInequalityGeneral Mathematicsmedia_common.quotation_subject010102 general mathematicsMathematics::Analysis of PDEs01 natural sciencesFunctional Analysis (math.FA)Sobolev spaceMathematics - Functional Analysis0103 physical sciencesFOS: Mathematics010307 mathematical physics0101 mathematicsepäyhtälötfunktionaalianalyysiComputer Science::DatabasesMathematicsmedia_common
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