Search results for "Monte Carlo molecular modeling"

showing 10 items of 63 documents

Cluster Expansions and Variational Monte Carlo in Medium Light Nuclei

1993

The B1 Brink-Boeker effective interaction is used to compute variational upper bounds for the ground state energy of nuclei from 16 O up to 40 Ca. The calculations are carried out by means of the Variational Monte Carlo method and with a multiplicative cluster expansion up to fourth order.

Hybrid Monte CarloPhysicsVariational methodQuantum Monte CarloQuantum electrodynamicsNuclear TheoryDynamic Monte Carlo methodVariational Monte CarloStatistical physicsGround stateMonte Carlo molecular modelingCluster expansion
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Path integral Monte Carlo study of the internal quantum state dynamics of a generic model fluid

1996

We study the quantum dynamics of a generic model fluid with internal quantum states and classical translational degrees of freedom in two spatial dimensions. The path integral Monte Carlo data for the imaginary time correlation functions are presented and analyzed by the maximum entropy method. A comparison of the frequency distribution with those of a mean field approximation and virial expansion shows good agreement at high and low densities, respectively. \textcopyright{} 1996 The American Physical Society.

Hybrid Monte CarloQuantum dynamicsQuantum Monte CarloMonte Carlo methodMonte Carlo integrationDiffusion Monte CarloStatistical physicsPath integral Monte CarloMathematicsMonte Carlo molecular modelingPhysical Review E
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Molecular-Level Characterization of Heterogeneous Catalytic Systems by Algorithmic Time Dependent Monte Carlo

2009

Monte Carlo algorithms and codes, used to study heterogeneous catalytic systems in the frame of the computational section of the NANOCAT project, are presented along with some exemplifying applications and results. In particular, time dependent Monte Carlo methods supported by high level quantum chemical information employed in the field of heterogeneous catalysis are focused. Technical details of the present algorithmic Monte Carlo development as well as possible evolution aimed at a deeper interrelationship of quantum and stochastic methods are discussed, pointing to two different aspects: the thermal-effect involvement and the three-dimensional catalytic matrix simulation. As topical app…

Hybrid Monte CarloTDMC catalytic propertiesChemistryMonte Carlo methodDynamic Monte Carlo methodMonte Carlo method in statistical physicsGeneral ChemistryStatistical physicsParallel temperingKinetic Monte CarloHeterogeneous catalysisCatalysisMonte Carlo molecular modelingTopics in Catalysis
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Monte Carlo simulation in phylogenies: an application to test the constancy of evolutionary rates.

1994

Monte Carlo simulation has commonly been used in phylogenetic studies to test different tree-reconstruction methods, and consequently, its application for testing evolutionary models can be considered as a natural extension of this usage. Repetitive simulation of a given evolutionary process, under the restrictions imposed by the model to be tested, along a determinate tree topology allow the estimate of probability distributions for the desired parameters. Next, the phylogenetic tree can be reconstructed again without the constraints of the model, and the parameter of interest, derived from this tree, can be compared to the corresponding probability distribution derived from the restricted…

Least-squares methodBiometryMonte Carlo methodCytochrome c GroupBiologySet (abstract data type)Hybrid Monte Carlosymbols.namesakeGeneticsAnimalsHumansComputer SimulationMolecular BiologyEcology Evolution Behavior and SystematicsMonte Carlo simulationPhylogenyPhylogenetic treeModels GeneticMolecular clockEvolutionary ratesMarkov chain Monte CarloTree (data structure)Genetic TechniquesMutationsymbolsProbability distributionCytochrome-cAlgorithmMonte Carlo MethodMonte Carlo molecular modelingParametric bootstrapJournal of molecular evolution
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Guide to Practical Work with the Monte Carlo Method

2002

The guide is structured such that we proceed from the “easy” simulation methods and algorithms to the more sophisticated. For each method the algorithms are presented by the technique of stepwise refinement. We first present the idea and the basic outline. From then on we proceed by breaking up the larger logical and algorithmic structures into smaller ones, until we have reached the level of single basic statements. Sometimes we may elect not to go to such a depth and the reader is asked to fill in the gaps.

Logical conjunctionComputer scienceMonte Carlo methodDynamic Monte Carlo methodIsing modelMonte Carlo method in statistical physicsRandom walkAlgorithmImportance samplingMonte Carlo molecular modeling
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Non-reversible Monte Carlo simulations of spin models

2011

Abstract Monte Carlo simulations are used to study simple systems where the underlying Markov chain satisfies the necessary condition of global balance but does not obey the more restrictive condition of detailed balance. Here, we show that non-reversible Markov chains can be set up that generate correct stationary distributions, but reduce or eliminate the diffusive motion in phase space typical of the usual Monte Carlo dynamics. Our approach is based on splitting the dynamics into a set of replicas with each replica representing a biased movement in reaction-coordinate space. This introduction of an additional bias in a given replica is compensated for by choosing an appropriate dynamics …

Markov chainMonte Carlo methodGeneral Physics and AstronomyDetailed balanceMarkov chain Monte Carlosymbols.namesakeHardware and ArchitecturesymbolsIsing modelStatistical physicsParallel temperingCritical exponentMathematicsMonte Carlo molecular modelingComputer Physics Communications
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On the adoption of the Monte Carlo method to solve one-dimensional steady state thermal diffusion problems for non-uniform solids

2013

Abstract The present paper is focussed on the investigation of the potential adoption of the Monte Carlo method to solve one-dimensional, steady state, thermal diffusion problems for continuous solids characterised by an isotropic, space-dependent conductivity tensor and subjected to non-uniform heat power deposition. To this purpose the steady state form of Fourier’s heat diffusion equation relevant to a continuous, heterogeneous and isotropic solid, undergoing a space-dependent heat power density has been solved in a closed analytical form for the general case of Cauchy’s boundary conditions. The thermal field obtained has been, then, put in a peculiar functional form, indicating that it …

Materials scienceApplied MathematicsQuantum Monte CarloMonte Carlo methodThermal diffusivityModeling and SimulationIsotropic solidDynamic Monte Carlo methodMonte Carlo method Heat diffusion Space-dependent thermal conductivityDiffusion Monte CarloHeat equationStatistical physicsSettore ING-IND/19 - Impianti NucleariMonte Carlo molecular modeling
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Monte Carlo Simulation of Crystal-Liquid Phase Coexistence

2016

When a crystal nucleus is surrounded by coexisting fluid in a finite volume in thermal equilibrium, the thermodynamic properties of the fluid (density, pressure, chemical potential) are uniquely related to the surface excess free energy of the nucleus. Using a model for weakly attractive soft colloidal particles, it is shown that this surface excess free energy can be determined accurately from Monte Carlo simulations over a wide range of nucleus volumes, and the resulting nucleation barriers are completely independent from the size of the total volume of the system. A necessary ingredient of the analysis, the pressure at phase coexistence in the thermodynamic limit, is obtained from the in…

Materials scienceMonte Carlo methodNucleation01 natural sciencesMolecular physics010305 fluids & plasmasHybrid Monte Carlo0103 physical sciencesThermodynamic limitDynamic Monte Carlo methodClassical nucleation theoryKinetic Monte Carlo010306 general physicsMonte Carlo molecular modeling
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A new strategy for effective learning in population Monte Carlo sampling

2016

In this work, we focus on advancing the theory and practice of a class of Monte Carlo methods, population Monte Carlo (PMC) sampling, for dealing with inference problems with static parameters. We devise a new method for efficient adaptive learning from past samples and weights to construct improved proposal functions. It is based on assuming that, at each iteration, there is an intermediate target and that this target is gradually getting closer to the true one. Computer simulations show and confirm the improvement of the proposed strategy compared to the traditional PMC method on a simple considered scenario.

Mathematical optimizationComputer scienceMonte Carlo methodInference02 engineering and technology01 natural sciencesHybrid Monte Carlo010104 statistics & probabilitysymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringQuasi-Monte Carlo methodKinetic Monte Carlo0101 mathematicsComputingMilieux_MISCELLANEOUSbusiness.industryRejection samplingSampling (statistics)020206 networking & telecommunicationsMarkov chain Monte CarloDynamic Monte Carlo methodsymbolsMonte Carlo integrationMonte Carlo method in statistical physicsArtificial intelligenceParticle filterbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMonte Carlo molecular modeling
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Monte Carlo tests of theoretical predictions for critical phenomena: still a problem?

2000

Two Monte Carlo studies of critical behavior in ferromagnetic Ising models are described: the first one deals with the crossover from the Ising class to the mean field class, when the interaction range increases. The second study deals with the finite size behavior at dimensionalities above the marginal dimension where Landau theory applies. The numerical results are compared to pertinent theoretical predictions, and unsolved problems are briefly described.

Mean field theoryHardware and ArchitectureCritical phenomenaMonte Carlo methodCrossoverGeneral Physics and AstronomyIsing modelMonte Carlo method in statistical physicsStatistical physicsLandau theoryMonte Carlo molecular modelingMathematicsComputer Physics Communications
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