A Guide to Monte Carlo Simulations in Statistical Physics

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Cambridge University Press, 2005 - Computers - 432 pages
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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.
 

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Contents

Some necessary background
7
Simple sampling Monte Carlo methods
48
Importance sampling Monte Carlo methods
68
More on importance sampling Monte Carlo methods
137
Offlattice models
194
Reweighting methods
251
Quantum Monte Carlo methods
277
Monte Carlo renormalization group methods
315
Nonequilibrium and irreversible processes
328
a brief introduction
350
A brief review of other methods of computer simulation
363
Monte Carlo methods outside of physics
383
Outlook
393
Index
427
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About the author (2005)

David P. Landau is the Distinguished Professor of Physics and Director of the Center for Simulational Physics at the University of Georgia.

Kurt Binder is Professor of Theoretical Physics at the Johannes-Gutenberg-University of Mainz, Germany.

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