A guide to Monte Carlo simulations in statistical physics

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. 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. This Book Will Be Bought By Graduate Students Who Have To Deal With Computer Simulations In Their Research, As Well As By Postdoctoral Researchers, In Both Physics And Physical Chemistry. It Can Be Used As A Textbook For Graduate Courses On Computer Simulations In Physics And Related Disciplines.--jacket. 1. Introduction -- 2. Some Necessary Background -- 3. Simple Sampling Monte Carlo Methods -- 4. Importance Sampling Monte Carlo Methods -- 5. More On Importance Sampling Monte Carlo Methods For Lattice Systems -- 6. Off-lattice Models -- 7. Reweighting Methods -- 8. Quantum Monte Carlo Methods -- 9. Monte Carlo Renormalization Group Methods -- 10. Non-equilibrium And Irreversible Processes -- 11. Lattice Gauge Models: A Brief Introduction -- 12. A Brief Review Of Other Methods Of Computer Simulation -- 13. Outlook -- App.: Listing Of Programs Mentioned In The Text. David P. Landau, Kurt Binder. Includes Bibliographical References And Index. This new and updated edition deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics, statistical mechanics, and related fields. After briefly recalling essential background in statistical mechanics and probability theory, it gives a succinct overview of simple sampling methods. The concepts behind the simulation algorithms are explained comprehensively, as are the techniques for efficient evaluation of system configurations generated by simulation. It contains many applications, examples, and exercises to help the reader and provides many new references to more specialized literature. This edition includes a brief overview of other methods of computer simulation and an outlook for the use of Monte Carlo simulations in disciplines beyond physics. This is an excellent guide for graduate students and researchers who use computer simulations in their research. It can be used as a textbook for graduate courses on computer simulations in physics and related disciplines. This book describes all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields, such as polymer science and lattice gauge theory. The authors give a succinct overview of simple sampling methods and develop the importance sampling method. In addition they introduce 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. The book includes many applications, examples, and current references, and exercises to help the reader. This book details Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields. The authors give a succinct overview of simple sampling-methods and develop the importance of sampling method.