Monte Carlo Simulation in Statistical Physics [Hardcover]

Kurt Binder (Author), Dieter W. Heermann (Author)

Book Description

Publication Date: August 26, 2002 | ISBN-10: 3540432213 | ISBN-13: 978-3540432210 | Edition: 4th, enlarged ed.

Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. This fourth edition has been updated and a new chapter on Monte Carlo simulation of quantum-mechanical problems has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was the winner of the Berni J. Alder CECAM Award for Computational Physics 2001.

Editorial Reviews

From the Back Cover

Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body systems in condensed-matter physics and related fields of physics, chemistry and beyond, to traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, probability distributions are calculated, allowing the estimation of the thermodynamic properties of various systems. This book describes the theoretical background to several variants of these Monte Carlo methods and gives a systematic presentation from which newcomers can learn to perform such simulations and to analyze their results. The fifth edition covers Classical as well as Quantum Monte Carlo methods. Furthermore a new chapter on the sampling of free-energy landscapes has been added. To help students in their work a special web server has been installed to host programs and discussion groups (http://wwwcp.tphys.uni-heidelberg.de). Prof. Binder was awarded the Berni J. Alder CECAM Award for Computational Physics 2001 as well as the Boltzmann Medal in 2007.  --This text refers to an alternate Hardcover edition.

Product Details

• Hardcover: 185 pages
• Publisher: Springer; 4th, enlarged ed. edition (August 26, 2002)
• Language: English
• ISBN-10: 3540432213
• ISBN-13: 978-3540432210
• Product Dimensions: 9.6 x 6.3 x 0.6 inches
• Shipping Weight: 14.1 ounces (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #2,991,228 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

7 of 7 people found the following review helpful:

4.0 out of 5 stars A graduate level book (Review for the 4th edition), March 8, 2007

By 

Peyman Khorsand (Irvine, CA United States) - See all my reviews
(REAL NAME)   

This review is from: Monte Carlo Simulation in Statistical Physics (Hardcover)

This is a nice little book written by two experts of the field. This edition is only an expanded version of earlier editions (by addition of two new chapters, the core of the book chapter 1 to 3 hasn't change at all). The book covers monte carlo techniques through various well-known examples (Ising model, random walk, percolation, self-avoiding random walk). I enjoyed reading the first 3 chapters of the book. In particular, chapter 3 guides the readers and gives them the chance to practice what they should have learned in previous chapter (through 53 exercises). The following 2 chapters (chapter 4 and 5) are not as nicely written. Moreover, there are some serious shortcoming in the book. (1) All codes are written in Fortran. While everyone who can program can easily understand the codes, Fortran belongs to the past and could have been ok for physics students during late 80's (first edition) but not for those at 2006. (2) The guide (chapter 3) should have been the last chapter and have covered subjects in chapters 4 and 5 (3) As I mentioned before, chapter 4 and 5 are not well-organized. (4) The book in general stresses too much on finite-size effects. However, it is an important subject and it tells us how we can scale our simulation result to more realistic cases. By my judgement, the book gives wrong impression about the degree of its importance.

I recommend graduate students who are serious about learning monte carlo methods to read Newman and Barkema book (Monte Carlo Methods in Statistical Physics) instead since it provides a broader view about the subject. Although I highly recommend those who are interested in the subject to go through chapter 3. It is fun and very instructive.