MARKOV CHAIN MONTE CARLO SIMULATIONS AND THEIR STATISTICAL ANALYSIS
With Web-Based Fortran Code
by Bernd A Berg (Florida State University, USA)
Download Fortran Code
Table of Contents (128k)
Preface (162k)
Chapter 1: Sampling, Statistics and Computer Code (1,516k)
(on the HTML) tar program
(on the separate link) gzip
(on the separate link) pdf file
(on the separate link) Download STMC.tgz (0.36 MB)
(on the separate link) Download MPIdata.tgz (1.25 MB)
(on the separate link) cygwin
(on the separate link) Gnuplot
This book teaches modern Markov chain Monte Carlo (MC) simulation techniques step by step. The material should be accessible to advanced undergraduate students and is suitable for a course. It ranges from elementary statistics concepts (the theory behind MC simulations), through conventional Metropolis and heat bath algorithms, autocorrelations and the analysis of the performance of MC algorithms, to advanced topics including the multicanonical approach, cluster algorithms and parallel computing. Therefore, it is also of interest to researchers in the field. The book relates the theory directly to Web-based computer code. This allows readers to get quickly started with their own simulations and to verify many numerical examples easily. The present code is in Fortran 77, for which compilers are freely available. The principles taught are important for users of other programming languages, like C or C++.
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