A Guide to Monte Carlo Simulati*** in Statistical Physics mobi 下载 网盘 caj lrf pdf txt 阿里云

This new and updated edition deals with all ***ects 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 *** sampling methods. The concepts behind the simulation algorithms are explained comprehensively, as are the techniques for efficient evaluation of system configurati*** generated by simulation. It contains many applicati***, examples, and exercises to help the reader and provides many new references to more specialized li***ture. This edition includes a brief overview of other methods of computer simulation and an outlook for the use of Monte Carlo simulati*** in disciplines beyond physics. This is an excellent guide for graduate students and researchers who use computer simulati*** in their research. It can be used as a textbook for graduate courses on computer simulati*** 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 Ge***ia.

　　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 ***ects 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

*** sampling methods. The concepts behind the simulation

algorithms are explained comprehensively, as are the techniques for

efficient evaluation of system configurati*** generated by

simulation. It contains many applicati***, examples, and exercises

to help the reader and provides many new references to more

specialized li***ture. This edition includes a brief overview of

other methods of computer simulation and an outlook for the use of

Monte Carlo simulati*** in disciplines beyond physics. This is an

excellent guide for graduate students and researchers who use

computer simulati*** in their research. It can be used as a

textbook for graduate courses on computer simulati*** in physics

and related disciplines.

书籍介绍

This new and updated edition deals with all ***ects 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 *** sampling methods. The concepts behind the simulation algorithms are explained comprehensively, as are the techniques for efficient evaluation of system configurati*** generated by simulation. It contains many applicati***, examples, and exercises to help the reader and provides many new references to more specialized li***ture. This edition includes a brief overview of other methods of computer simulation and an outlook for the use of Monte Carlo simulati*** in disciplines beyond physics. This is an excellent guide for graduate students and researchers who use computer simulati*** in their research. It can be used as a textbook for graduate courses on computer simulati*** in physics and related disciplines.