Search results for "Carlo"

showing 10 items of 1845 documents

Rejection-Free Monte Carlo

2019

So far, we have been using the rejection Monte Carlo algorithms. To remind us, the algorithms proceed from state x to possible state \(x'\) as outlined in Algorithm 1.

Computer scienceMonte Carlo methodStatistical physicsState (functional analysis)
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Theoretical Foundations of the Monte Carlo Method and Its Applications in Statistical Physics

2002

In this chapter we first introduce the basic concepts of Monte Carlo sampling, give some details on how Monte Carlo programs need to be organized, and then proceed to the interpretation and analysis of Monte Carlo results.

Computer scienceMonte Carlo methodThermodynamic limitPeriodic boundary conditionsMonte Carlo method in statistical physicsIsing modelStatistical physicsImportance samplingMonte Carlo molecular modelingInterpretation (model theory)
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Path Integral approach via Laplace’s method of integration for nonstationary response of nonlinear systems

2019

In this paper the nonstationary response of a class of nonlinear systems subject to broad-band stochastic excitations is examined. A version of the Path Integral (PI) approach is developed for determining the evolution of the response probability density function (PDF). Specifically, the PI approach, utilized for evaluating the response PDF in short time steps based on the Chapman–Kolmogorov equation, is here employed in conjunction with the Laplace’s method of integration. In this manner, an approximate analytical solution of the integral involved in this equation is obtained, thus circumventing the repetitive integrations generally required in the conventional numerical implementation of …

Computer sciencePath IntegralMonte Carlo methodMarkov processProbability density function02 engineering and technologyNonstationary response01 natural sciencessymbols.namesake0203 mechanical engineering0103 physical sciencesProbability density functionApplied mathematics010301 acousticsVan der Pol oscillatorLaplace transformMechanical EngineeringEvolutionary excitationLaplace’s methodCondensed Matter PhysicsNonlinear system020303 mechanical engineering & transportsMechanics of MaterialsLaplace's methodPath integral formulationsymbolsSettore ICAR/08 - Scienza Delle Costruzioni
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Modeling Snow Dynamics Using a Bayesian Network

2015

In this paper we propose a novel snow accumulation and melt model, formulated as a Dynamic Bayesian Network DBN. We encode uncertainty explicitly and train the DBN using Monte Carlo analysis, carried out with a deterministic hydrology model under a wide range of plausible parameter configurations. The trained DBN was tested against field observations of snow water equivalents SWE. The results indicate that our DBN can be used to reason about uncertainty, without doing resampling from the deterministic model. In all brevity, the DBN's ability to reproduce the mean of the observations was similar to what could be obtained with the deterministic hydrology model, but with a more realistic repre…

Computer scienceResamplingMonte Carlo methodRange (statistics)Bayesian networkComputer Science::Artificial IntelligenceSnowRepresentation (mathematics)AlgorithmField (computer science)Dynamic Bayesian networkSimulation
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Testing for goodness rather than lack of fit of continuous probability distributions.

2021

The vast majority of testing procedures presented in the literature as goodness-of-fit tests fail to accomplish what the term is promising. Actually, a significant result of such a test indicates that the true distribution underlying the data differs substantially from the assumed model, whereas the true objective is usually to establish that the model fits the data sufficiently well. Meeting that objective requires to carry out a testing procedure for a problem in which the statement that the deviations between model and true distribution are small, plays the role of the alternative hypothesis. Testing procedures of this kind, for which the term tests for equivalence has been coined in sta…

Computer scienceStatement (logic)Alternative hypothesisScienceTest StatisticsResearch and Analysis MethodsStatistical InferenceMathematical and Statistical TechniquesStatistical inferenceEconometricsHumansLack-of-fit sum of squaresStatistical MethodsEquivalence (measure theory)Statistical hypothesis testingStatistical DataProbabilityMultidisciplinaryModels StatisticalApplied MathematicsSimulation and ModelingStatisticsQRProbability TheoryProbability DistributionTerm (time)Monte Carlo methodStatistical TheoriesPhysical SciencesProbability distributionMedicineMathematicsAlgorithmsResearch ArticleStatistical DistributionsPLoS ONE
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Quantum Monte Carlo study of high pressure solid molecular hydrogen

2013

We use the diffusion quantum Monte Carlo (DMC) method to calculate the ground state phase diagram of solid molecular hydrogen and examine the stability of the most important insulating phases relative to metallic crystalline molecular hydrogen. We develop a new method to account for finite-size errors by combining the use of twist-averaged boundary conditions with corrections obtained using the Kwee-Zhang-Krakauer (KZK) functional in density functional theory. To study band-gap closure and find the metallization pressure, we perform accurate quasi-particle many-body calculations using the $GW$ method. In the static approximation, our DMC simulations indicate a transition from the insulating…

Condensed Matter - Materials Science540 Chemistry and allied sciencesMaterials scienceCondensed matter physicsBand gapQuantum Monte CarloClose-packing of equal spheresMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesGeneral Physics and Astronomy540 ChemieDensity functional theoryBoundary value problemDiffusion (business)Ground statePhase diagram
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Fluctuating Interfaces in Liquid Crystals

2008

We review and compare recent work on the properties of fluctuating interfaces between nematic and isotropic liquid-crystalline phases. Molecular dynamics and Monte Carlo simulations have been carried out for systems of ellipsoids and hard rods with aspect ratio 15:1, and the fluctuation spectrum of interface positions (the capillary wave spectrum) has been analyzed. In addition, the capillary wave spectrum has been calculated analytically within the Landau-de Gennes theory. The theory predicts that the interfacial fluctuations can be described in terms of a wave vector dependent interfacial tension, which is anisotropic at small wavelengths (stiff director regime) and becomes isotropic at l…

Condensed Matter - Materials ScienceCapillary wavePolymers and PlasticsCondensed matter physicsChemistryOrganic ChemistryIsotropyMonte Carlo methodMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesCondensed Matter - Soft Condensed MatterCondensed Matter Physics01 natural sciencesLandau theory010305 fluids & plasmasCondensed Matter::Soft Condensed MatterWavelengthLiquid crystal0103 physical sciencesMaterials ChemistrySoft Condensed Matter (cond-mat.soft)010306 general physicsAnisotropyFluctuation spectrumMacromolecular Symposia
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Evidence of nickel ions dimerization in NiWO$_4$ and NiWO$_4$-ZnWO$_4$ solid solutions probed by EXAFS spectroscopy and reverse Monte Carlo simulatio…

2021

G.B. acknowledges the financial support provided by the State Education Development Agency for project No.1.1.1.2/VIAA/3/19/444 (agreement No. 1.1.1.2/16/I/001) realized at the Institute of Solid State Physics, University of Latvia. A.K. and A.K. would like to thank the support of the Latvian Council of Science project No. lzp-2019/1-0071. Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART2.

Condensed Matter - Materials ScienceEXAFSNiWO4solid solutions:NATURAL SCIENCES:Physics [Research Subject Categories]Materials Science (cond-mat.mtrl-sci)FOS: Physical sciencesZnWO4antiferromagnetsreverse Monte Carlo
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Speeding up of microstructure reconstruction: II. Application to patterns of poly-dispersed islands

2015

We report a fast, efficient and credible statistical reconstruction of any two-phase patterns of islands of miscellaneous shapes and poly-dispersed in sizes. In the proposed multi-scale approach called a weighted doubly-hybrid, two different pairs of hybrid descriptors are used. As the first pair, we employ entropic quantifiers, while correlation functions are the second pair. Their competition allows considering a wider spectrum of morphological features. Instead of a standard random initial configuration, a synthetic one with the same number of islands as that of the target is created by a cellular automaton. This is the key point for speeding-up of microstructure reconstruction, making u…

Condensed Matter - Materials ScienceGeneral Computer ScienceStatistical Mechanics (cond-mat.stat-mech)Interface (Java)Computer scienceMonte Carlo methodGeneral Physics and AstronomyMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesGeneral ChemistryMicrostructureSample (graphics)Cellular automatonOutcome (probability)Computational MathematicsKey pointMechanics of MaterialsSimulated annealingGeneral Materials ScienceAlgorithmCondensed Matter - Statistical Mechanics
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Peculiarities of the local structure in new medium- and high-entropy, low-symmetry tungstates

2022

G. Bakradze acknowledges financial support provided by the Latvian Council of Science for project no. 1.1.1.2/VIAA/3/19/444 (agreement no. 1.1.1.2/16/I/001) realized at the Institute of Solid State Physics, University of Latvia. The Institute of Solid State Physics, University of Latvia, as a centre of excellence, has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement no. 739508, project CAMART2.

Condensed Matter - Materials ScienceHigh-entropy oxidesMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciences:NATURAL SCIENCES::Physics [Research Subject Categories]TungstatesGeneral ChemistryCondensed Matter Physics540ddc:540Reverse Monte Carlo methodGeneral Materials ScienceSolid solutionsExtended X-ray absorption fine structure
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