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This book deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics as well as in related fields, for example polymer science and lattice gauge theory. After briefly recalling essential background in statistical mechanics and probability theory, the authors give a succinct overview of simple sampling methods. The next several chapters develop the importance sampling method. The concepts behind the various simulation algorithms are explained. The fact that simulations deal with small systems is emphasized. Other chapters also provide introductions to quantum Monte Carlo methods, aspects of simulations of growth phenomena and other systems far from equilibrium, and the Monte Carlo Renormalization Group approach to critical phenomena. Throughout the book there are many applications, examples, and exercises to help the reader in a thorough study of this book; furthermore, up-to-date references to more specialized literature are also provided.
Statistical physics --- Mathematical physics --- Monte Carlo method. --- Statistical physics. --- Monte Carlo method --- Monte-Carlo, Méthode de --- Physique statistique
Choose an application
This book deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics as well as in related fields, for example polymer science and lattice gauge theory. It includes many applications, examples, and exercises throughout.
Monte Carlo method. --- Statistical physics. --- Artificial sampling --- Model sampling --- Monte Carlo simulation --- Monte Carlo simulation method --- Stochastic sampling --- Games of chance (Mathematics) --- Mathematical models --- Numerical analysis --- Numerical calculations --- Stochastic processes --- Physics --- Mathematical statistics --- Statistical methods
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