A Guide to Monte Carlo Simulations in Statistical Physics
Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. This edition now contains material describing powerful new algorithms that have appeared since the previous edition was published, and highlights recent technical advances and key applications that these algorithms now make possible. Updates also include several new sections and a chapter on the use of Monte Carlo simulations of biological molecules. Throughout the book there are many applications, examples, recipes, case studies, and exercises to help the reader understand the material. It is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.
- Contains material describing powerful new algorithms, recent technical advances and key applications
- Deals with all aspects of Monte Carlo simulation encountered in condensed-matter physics and statistical mechanics
- Includes many applications, examples, recipes, case studies, and exercises to help the reader understand the material
Reviews & endorsements
Review of the first edition: 'This book will serve as a useful introduction to those entering the field, while for those already versed in the subject it provides a timely survey of what has been achieved.' D. C. Rapaport, Journal of Statistical Physics
Product details
November 2009Adobe eBook Reader
9780511629754
0 pages
0kg
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- Preface
- 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 of 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. Monte Carlo simulations at the periphery of physics and beyond
- 14. Monte Carlo studies of biological molecules
- 15. Outlook
- Appendix
- Index.