An Introduction to Monte Carlo Simulations in Statistical Physics
by K. P. N. Murthy
Publisher: arXiv 2003
Number of pages: 92
A brief introduction to the technique of Monte Carlo simulations in statistical physics is presented. The topics covered include statistical ensembles random and pseudo random numbers, random sampling techniques, importance sampling, Markov chain, Metropolis algorithm, continuous phase transition, statistical errors from correlated and uncorrelated data, finite size scaling, n-fold way, critical slowing down, blocking technique,percolation, cluster algorithms, etc.
Home page url
Download or read it online for free here:
by J. L. Garcia-Palacios - arXiv
Contents: Stochastic variables; Stochastic processes and Markov processes; The master equation; The Langevin equation; Linear response theory, dynamical susceptibilities, and relaxation times; Langevin and Fokker–Planck equations; etc.
by S.N. Dorogovtsev, J.F.F. Mendes - arXiv
The authors review the recent fast progress in statistical physics of evolving networks. Interest has focused mainly on the structural properties of random complex networks in communications, biology, social sciences and economics.
by V.I. Yukalov - arXiv
The review is devoted to the elucidation of the basic problems arising in the theoretical investigation of systems with Bose-Einstein condensate. Understanding these problems is necessary for the correct description of Bose-condensed systems.
by Paul Fendley - The University of Virginia
This book is an attempt to cover the gap between what is taught in a conventional statistical mechanics class and between what is necessary to understand current research. The aim is to introduce the basics of many-body physics to a wide audience.