Search results for "monte carlo simulations"

showing 10 items of 37 documents

Characterization and performance of the DTAS detector

2018

11 pags., 16 figs., 3 tabs.

Nuclear and High Energy PhysicsPhysics - Instrumentation and DetectorsPhysics::Instrumentation and DetectorsAstrophysics::High Energy Astrophysical PhenomenaMonte Carlo methodspektrometritβ decayFOS: Physical sciencesNon-proportional scintillation light yield: Monte Carlo simulationsMonte Carlo simulations [Non-proportional scintillation light yield]y-ray spectrometerB decay[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]01 natural sciencesMonte Carlo simulationsOpticsDistortion0103 physical sciencesNeutron[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]Nuclear Experiment (nucl-ex)010306 general physicsAbsorption (electromagnetic radiation)Nuclear ExperimentInstrumentation[formula omitted] decayNuclear ExperimentPhysicsta114Spectrometer010308 nuclear & particles physicsbusiness.industryNaI(Tl) detectorPulse generatorTotal absorption [formula omitted]-ray spectrometerDetectornon-proportional scintillation light yieldInstrumentation and Detectors (physics.ins-det)Total absorption γ -ray spectrometerNon-proportional scintillation light yieldFísica nuclearTotal absorptionydinfysiikkabusinessDelayed neutronExotic nucleiNuclear instruments & methods inphysics research section A: Accelerators spectrometers detectors and associated equipment 910: 79-89 (2018)
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The Monte Carlo simulation of the Borexino detector

2017

We describe the Monte Carlo (MC) simulation package of the Borexino detector and discuss the agreement of its output with data. The Borexino MC 'ab initio' simulates the energy loss of particles in all detector components and generates the resulting scintillation photons and their propagation within the liquid scintillator volume. The simulation accounts for absorption, reemission, and scattering of the optical photons and tracks them until they either are absorbed or reach the photocathode of one of the photomultiplier tubes. Photon detection is followed by a comprehensive simulation of the readout electronics response. The algorithm proceeds with a detailed simulation of the electronics c…

Physics - Instrumentation and DetectorsPhysics::Instrumentation and DetectorsSolar neutrinoMonte Carlo methodscintillation counter: liquidSolar neutrinosenergy resolution01 natural sciences7. Clean energyLarge volume liquid scintillator detectorHigh Energy Physics - Experiment[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Large volume liquid scintillator detectorsBorexinoPhysicsphotomultipliertrack data analysisDetectorefficiency: quantumddc:540GEANTBorexinoNeutrinophoton: yieldnumerical calculations: Monte CarloPhotomultiplierdata analysis methodenergy lossScintillatorSolar neutrinoprogrammingphoton: reflectionMonte Carlo simulationsNuclear physics0103 physical sciencesphoton: scattering[INFO]Computer Science [cs][PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]010306 general physicsbackground: radioactivityMonte Carlo simulationdetector: designScintillation010308 nuclear & particles physicsbibliographyAstronomy and AstrophysicscalibrationLarge volume liquid scintillator detectors; Monte Carlo simulations; Solar neutrinos; Astronomy and Astrophysicsattenuation: lengthpile-upelectronics: readout
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Electron dynamical response in InP semiconductors driven by fluctuating electric fields

2015

Abstract The complexity of electron dynamics in low-doped n-type InP crystals operating under fluctuating electric fields is deeply explored and discussed. In this study, we employ a multi-particle Monte Carlo approach to simulate the non-linear transport of electrons inside the semiconductor bulk. All possible scattering events of hot electrons in the medium, the main details of the band structure, as well as the heating effects, are taken into account. The results presented in this study derive from numerical simulations of the electron dynamical response to the application of a sub-Thz electric field, fluctuating for the superimposition of an external source of Gaussian correlated noise.…

PhysicsNoise powerCondensed matter physicsField (physics)Anomalous diffusionGeneral MathematicsApplied MathematicsGeneral Physics and AstronomyStatistical and Nonlinear PhysicsElectronNoise (electronics)Noise processes and phenomena High field and nonlinear effects Monte Carlo simulations Electron transportSettore FIS/03 - Fisica Della MateriaSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Correlation function (statistical mechanics)AmplitudeElectric field
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Memory expansion for diffusion coefficients

1998

We present a memory expansion for macroscopic transport coefficients such as the collective and tracer diffusion coefficients ${D}_{C}$ and ${D}_{T},$ respectively. The successive terms in this expansion for ${D}_{C}$ describe rapidly decaying memory effects of the center-of-mass motion, leading to fast convergence when evaluated numerically. For ${D}_{T},$ one obtains an expansion of similar form that contains terms describing memory effects in single-particle motion. As an example we evaluate ${D}_{C}$ and ${D}_{T}$ for three strongly interacting surface systems through Monte Carlo simulations, and for a simple model diffusion system via molecular dynamics calculations. We show that the n…

PhysicsSurface (mathematics)SpeedupNumerical analysisPhysicsMonte Carlo methodmacroscopic transport coefficients02 engineering and technology021001 nanoscience & nanotechnologysurface systems01 natural sciencesMonte Carlo simulationsMolecular dynamics0103 physical sciencesConvergence (routing)numerical methodsDiffusion (business)010306 general physics0210 nano-technologyOrder of magnitudeMathematical physicsmemory expansions
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Global sensitivity analysis for micropollutant modeling by means of an urban integrated approach

2015

The paper presents the sensitivity analysis of an integrated urban water quality system by means of the global sensitivity analysis (GSA). Specifically, an home-made integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole - SMX). The model is able to estimate also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and the receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Five scenarios each characterized by different combinations of sub-systems (i.e., SS, WWTP an…

Settore ICAR/03 - Ingegneria Sanitaria-AmbientaleContaminants of emerging concerns mathematical modelling Monte Carlo simulations sensitivity analysis urban water quality.
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Weighted-Average Least Squares (WALS): Confidence and Prediction Intervals

2022

We extend the results of De Luca et al. (2021) to inference for linear regression models based on weighted-average least squares (WALS), a frequentist model averaging approach with a Bayesian flavor. We concentrate on inference about a single focus parameter, interpreted as the causal effect of a policy or intervention, in the presence of a potentially large number of auxiliary parameters representing the nuisance component of the model. In our Monte Carlo simulations we compare the performance of WALS with that of several competing estimators, including the unrestricted least-squares estimator (with all auxiliary regressors) and the restricted least-squares estimator (with no auxiliary reg…

Shrinkage estimatorStatistics::TheorySettore SECS-P/05Economics Econometrics and Finance (miscellaneous)Linear model WALS condence intervals prediction intervals Monte Carlo simulations.Prediction intervalEstimatorSettore SECS-P/05 - EconometriaComputer Science ApplicationsLasso (statistics)Frequentist inferenceBayesian information criterionStatisticsStatistics::MethodologyAkaike information criterionJackknife resamplingMathematics
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A Stochastic Approach to Quantum Statistics Distributions: Theoretical Derivation and Monte Carlo Modelling

2009

Abstract. We present a method aimed at a stochastic derivation of the equilibrium distribution of a classical/quantum ideal gas in the framework of the canonical ensemble. The time evolution of these ideal systems is modelled as a series of transitions from one system microstate to another one and thermal equilibrium is reached via a random walk in the single-particle state space. We look at this dynamic process as a Markov chain satisfying the condition of detailed balance and propose a variant of the Monte Carlo Metropolis algorithm able to take into account indistinguishability of identical quantum particles. Simulations performed on different two-dimensional (2D) systems are revealed to…

Statistics and ProbabilityCanonical ensemblePhysicsclassical Monte Carlo simulations quantum Monte Carlo simulations stochastic particle dynamics (theory)Monte Carlo methodStatistical and Nonlinear PhysicsMarkov chain Monte CarloIdeal gasMicrostate (statistical mechanics)symbols.namesakeThermodynamic limitDynamic Monte Carlo methodsymbolsStatistical physicsStatistics Probability and UncertaintyQuantum statistical mechanics
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Island Diffusion on Metal fcc (100) Surfaces

1999

We present Monte Carlo simulations for the size and temperature dependence of the diffusion coefficient of adatom islands on the Cu(100) surface. We show that the scaling exponent for the size dependence is not a constant but a decreasing function of the island size and approaches unity for very large islands. This is due to a crossover from periphery dominated mass transport to a regime where vacancies diffuse inside the island. The effective scaling exponents are in good agreement with theory and experiments.

Surface (mathematics)Condensed Matter - Materials ScienceMaterials scienceCondensed matter physicsPhysicsCrossoverMonte Carlo methodMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesGeneral Physics and Astronomyfcc(100) surfaceFunction (mathematics)Monte Carlo simulationsadatomAlisland diffusionExponentDiffusion (business)Constant (mathematics)ScalingCuPhysical Review Letters
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Highly Defined, Colloid‐Like Ionic Clusters in Solution

2012

Many societal challenges at the beginning of the 21st century lead to an apparent and growing need for functional materials and novel ways of materials synthesis and assembly. Rising to the challenge, the utilization of small, self-assembling building blocks for the bottom-up construction of new types of polymers and nanostructures has enjoyed increasing popularity among materials researchers in the recent past. Supramolecular materials like foldamers, surface films, nanoparticles, etc. are created by exploiting noncovalent forces [1] leading to an ordered arrangement of nanoscale building blocks. [2] In the search for new polymers based on noncovalent molecular forces, we are motivated by …

chemistry.chemical_classificationNanostructureChemistrySupramolecular chemistryNanoparticleIonic bondingdynamic light scatteringNanotechnologyself-assemblyGeneral ChemistryPolymerCommunicationsmolecular dynamicsnanoscale electrostaticsMonte Carlo simulationsSupramolecular polymersMolecular dynamicsSelf-assemblyChemistryOpen
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Third virial coefficient for 4-arm and 6-arm star polymers

2008

We discuss the computation of the third virial coefficient in polymer systems, focusing on an additional contribution absent in the case of monoatomic fluids. We determine the interpenetration ratio and several quantities that involve the third virial coefficient for star polymers with 4 and 6 arms in the good-solvent regime, in the limit of a large degree of polymerization.

chemistry.chemical_classificationPhysicsMonatomic gasStatistical Mechanics (cond-mat.stat-mech)Polymers and PlasticsOrganic ChemistryMonte Carlo methodFOS: Physical sciencesThermodynamicsPolymerStatistical mechanicsDegree of polymerizationCondensed Matter - Soft Condensed MatterCondensed Matter Physicsmonte carlo simulations; star polymers; statistical mechanics; statistical thermodynamics; virial expansionInorganic ChemistrychemistryVirial coefficientMaterials ChemistryVirial expansionSoft Condensed Matter (cond-mat.soft)Limit (mathematics)Condensed Matter - Statistical Mechanics
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