Monte Carlo Methods in Statistical Physics - Couverture souple

Newman, M. E. J.

Couverture souple

ISBN 10 : 0198517971 ISBN 13 : 9780198517979

Editeur : Oxford University Press, U.S.A., 1999

Synopsis

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.

A propos du livre

Présentation de l'éditeur

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.

Biographie de l'auteur

Mark Newman is at Santa Fe Institute. G. T. Barkema is at Utrecht University.

Détails de l'édition

• Éditeur: Oxford University Press, U.S.A.
• Date d'édition: 1999
• Langue: anglais
• ISBN 10: 0198517971
• ISBN 13: 9780198517979
• Reliure: Broché
• Nombre de pages: 496
• Coordonnées du fabricant: non disponible
• Personne responsable: Ufficio Anagrafiche Messaggerie; ufficio.anagrafiche@meli.it; ; Via Verdi, 8; Assago Milano; 20090; Italie