A Guide to Monte Carlo Simulations in Statistical Physics

Nonfiction, Science & Nature, Science, Physics, Mathematical Physics, General Physics
Cover of the book A Guide to Monte Carlo Simulations in Statistical Physics by David P. Landau, Kurt Binder, Cambridge University Press
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Author: David P. Landau, Kurt Binder ISBN: 9781139636698
Publisher: Cambridge University Press Publication: September 10, 2009
Imprint: Cambridge University Press Language: English
Author: David P. Landau, Kurt Binder
ISBN: 9781139636698
Publisher: Cambridge University Press
Publication: September 10, 2009
Imprint: Cambridge University Press
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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