A Guide to Monte Carlo Simulations in Statistical Physics 阿里云 kindle 下载 pdf chm 百度云 azw3 umd

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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　　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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　　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.

书籍介绍

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.