Topic
Dynamic Monte Carlo method
About: Dynamic Monte Carlo method is a research topic. Over the lifetime, 13294 publications have been published within this topic receiving 371256 citations.
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IBM1
TL;DR: Near-optimal strategies are developed for estimating the free energy difference between two canonical ensembles, given a Metropolis-type Monte Carlo program for sampling each one, and their efficiency is never less or greater than that obtained by sampling only one ensemble.
2,347 citations
TL;DR: In this paper, a new method for using the data from Monte Carlo simulations that can increase the efficiency by 2 or more orders of magnitude is presented. But the method is not applicable to statistical models and lattice-gauge theories.
Abstract: We present a new method for using the data from Monte Carlo simulations that can increase the efficiency by 2 or more orders of magnitude. A single Monte Carlo simulation is sufficient to obtain complete thermodynamic information over the entire scaling region near a phase transition. The accuracy of the method is demonstrated by comparison with exact results for the d=2 Ising model. New results for d=2 eight-state Potts model are also presented. The method is generally applicable to statistical models and lattice-gauge theories.
2,219 citations
Book•
05 Dec 2012
TL;DR: This paper presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging samples and generating random numbers.
Abstract: Introduction.- Estimating Volume and Count.- Generating Samples.- Increasing Efficiency.- Random Tours.- Designing and Analyzing Sample Paths.- Generating Pseudorandom Numbers.
2,215 citations
TL;DR: In this article, the authors present a method for optimizing the analysis of data from multiple Monte Carlo computer simulations over wide ranges of parameter values, which is applicable to simulations in lattice gauge theories, chemistry, and biology, as well as statistical mechanics.
Abstract: We present a new method for optimizing the analysis of data from multiple Monte Carlo computer simulations over wide ranges of parameter values. Explicit error estimates allow objective planning of the lengths of runs and the parameter values to be simulated. The method is applicable to simulations in lattice gauge theories, chemistry, and biology, as well as statistical mechanics.
2,198 citations
TL;DR: In this paper, the basic principles of the Monte Carlo method, as applied to the solution of transport problems in semiconductors, are presented in a comprehensive and tutorial form, with the aim of showing the power of the method in obtaining physical insights into the processes under investigation.
Abstract: This review presents in a comprehensive and tutorial form the basic principles of the Monte Carlo method, as applied to the solution of transport problems in semiconductors. Sufficient details of a typical Monte Carlo simulation have been given to allow the interested reader to create his own Monte Carlo program, and the method has been briefly compared with alternative theoretical techniques. Applications have been limited to the case of covalent semiconductors. Particular attention has been paid to the evaluation of the integrated scattering probabilities, for which final expressions are given in a form suitable for their direct use. A collection of results obtained with Monte Carlo simulations is presented, with the aim of showing the power of the method in obtaining physical insights into the processes under investigation. Special technical aspects of the method and updated microscopic models have been treated in some appendixes.
2,081 citations