- Inbunden (Hardback)
- Antal sidor
- Cambridge University Press
- Binder, Kurt
- 172 b/w illus.
- 251 x 168 x 25 mm
- Antal komponenter
- 69:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Case Laminate on White w/Gloss Lam
- 1203 g
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A Guide to Monte Carlo Simulations in Statistical Physics669Skickas inom 7-10 vardagar.
Gratis frakt inom Sverige över 159 kr för privatpersoner.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 fourth edition contains extensive new material describing numerous powerful algorithms not covered in previous editions, in some cases representing new developments that have only recently appeared. Older methodologies whose impact was previously unclear or unappreciated are also introduced, in addition to many small revisions that bring the text and cited literature up to date. This edition also introduces the use of petascale computing facilities in the Monte Carlo arena. 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.
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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
David P. Landau is the Distinguished Research Professor of Physics and founding Director of the Center for Simulational Physics at the University of Georgia, USA. Kurt Binder is Professor Emeritus of Theoretical Physics and Gutenberg Fellow at the Institut fr Physik, Johannes Gutenberg Universitt, Mainz, Germany.
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. Monte Carlo simulations at the periphery of physics and beyond; 14. Monte Carlo studies of biological molecules; 15. Outlook; Appendix: listing of programs mentioned in the text; Index.