Monte Carlo Methods in Statistical Physics

by Mark Newman and G T Barkema

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Book cover for Monte Carlo Methods in Statistical Physics

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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 programmes demonstrating the applications of these techniques to a variety of well-known models.
  • ISBN10 6610758913
  • ISBN13 9786610758913
  • Publish Date 1 January 1999
  • Publish Status Active
  • Out of Print 17 July 2012
  • Publish Country US
  • Imprint Oxford University Press
  • Format eBook
  • Pages 496
  • Language English