Monte Carlo Methods in Statistical Physics

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Overview

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. It includes methods for both equilibrium and out of equilibrium systems, and discusses in detail such common algorithms as the Metropolis and heat-bath algorithms, 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 lattice representations, efficient implementation of data structures, multispin coding, parallelization of Monte Carlo algorithms, and random number generation. The book also includes example programs which show how to apply these techniques to a variety of well-known models.

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Product Details

  • ISBN-13: 9780198517962
  • Publisher: Oxford University Press, USA
  • Publication date: 5/1/1999
  • Pages: 490
  • Product dimensions: 6.14 (w) x 9.21 (h) x 0.43 (d)

Meet the Author

Santa Fe Institute

Utrecht University

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Table of Contents

I Equilibrium Monte Carlo simulations
1 Introduction 3
2 The principles of equilibrium thermal Monte Carlo simulation 31
3 The Ising model and the Metropolis algorithm 45
4 Other algorithms for the Ising model 87
5 The conserved-order-parameter Ising model 133
6 Disordered spin models 151
7 Ice models 179
8 Analysing Monte Carlo data 210
II Out-of-equilibrium simulations
9 Out-of-equilibrium Monte Carlo simulations 263
10 Non-equilibrium simulations of the Ising model 268
11 Monte Carlo simulations in surface science 289
12 The repton model 307
III Implementation
13 Lattices and data structures 331
14 Monte Carlo simulations on parallel computers 356
15 Multispin coding 364
16 Random numbers 382
References 410
App. A Answers to problems 417
App. B Sample programs 433
Index 455
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