Monte Carlo Methods in Statistical Physics

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ID: 290012
1999
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Abstract
Abstract This book provides an introduction to Monte Carlo simulations in classical statistical physics and is aimed both at students beginning work in the field and at more experienced researchers who wish to learn more about Monte Carlo methods. The material covered includes methods for both equilibrium and out of equilibrium systems, and common algorithms like the Metropolis and heat-bath algorithms are discussed in detail, as well as more sophisticated ones such as continuous time Monte Carlo, cluster algorithms, multigrid methods, entropic sampling and simulated tempering. Data analysis techniques are also explained starting with straightforward measurement and error-estimation techniques and progressing to topics such as the single and multiple histogram methods and finite size scaling. The last few chapters of the book are devoted to implementation issues, including discussions of such topics as lattice representations, efficient implementation of data structures, multispin coding, parallelization of Monte Carlo algorithms, and random number generation. At the end of the book the authors give a number of example programs demonstrating the applications of these techniques to a variety of well-known models.
Reference Key
openalex_W1666636243 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors M. E. J. Newman, G. T. Barkema
Journal Oxford University Press eBooks
Year 1999
DOI
10.1093/oso/9780198517962.001.0001
URL
https://doi.org/10.1093/oso/9780198517962.001.0001
Keywords Keywords not found

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