Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms

@inproceedings{Sokal1997MonteCM,
  title={Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms},
  author={Alan D. Sokal},
  year={1997}
}
These notes are an updated version of lectures given at the Cours de Troisieme Cycle de la Physique en Suisse Romande (Lausanne, Switzerland) in June 1989. We thank the Troisieme Cycle de la Physique en Suisse Romande and Professor Michel Droz for kindly giving permission to reprint these notes. 
Cluster Monte Carlo Algorithms and Their Applications
TLDR
The Markov chain Monte Carlo method is introduced and the background of the cluster algorithms in statistical physics, a type of cluster algorithms that update dynamical variables in a global fashion, is reviewed.
Monte Carlo Methods
Convergence and Mixing in Markov Chain Monte Carlo: Advanced Algorithms and Latest Developments
We survey possible strategies to improve the performance of Markov chain Monte Carlo methods either by reducing the asymptotic variance of the resulting estimators or by increasing the speed of
Monte Carlo simulation and population-based optimization
  • A. Cercueil, O. François
  • Computer Science
    Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546)
  • 2001
TLDR
Some properties of Monte Carlo simulation are reviewed and the link to evolutionary computation is emphasized, showing how this connection can help to study evolutionary algorithms within a unified framework.
5 Introduction to Simulation Techniques
These lectures give an introduction to Monte Carlo simulations of classical statistical physics systems and their statistical analysis. After briefly recalling a few elementary properties of phase
Monte Carlo methods
TLDR
The basic principles and the most common Monte Carlo algorithms are reviewed, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC) methods are reviewed.
Monte Carlo Methods in Classical Statistical Physics
TLDR
After first discussing simulated and parallel tempering methods, finally also the alternative approach using multicanonical ensembles and the Wang-Landau recursion are briefly outlined.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 196 REFERENCES
Dynamic correlations in the three-dimensional Ising model.
Emploi de simulations de Monte Carlo pour mesurer les temps de correlation a l'equilibre de reseaux d'Ising de dimensions finies a la temperature critique en volume. La valeur mesuree par l'exposant
Monte Carlo Methods
1 The general nature of Monte Carlo methods.- 2 Short resume of statistical terms.- 3 Random, pseudorandom, and quasirandom numbers.- 4 Direct simulation.- 5 General principles of the Monte Carlo
Nonuniversal critical dynamics in Monte Carlo simulations.
A new approach to Monte Carlo simulations is presented, giving a highly efficient method of simulation for large systems near criticality. The algorithm violates dynamic universality at second-order
Molecular Dynamics and Monte Carlo Calculations in Statistical Mechanics
Monte Carlo and molecular dynamics calculations on statistical mechanical systems is reviewed giving some of the more significant recent developments. It is noted that the term molecular dynamics
General cluster updating method for Monte Carlo simulations.
  • Niedermayer
  • Physics, Medicine
    Physical review letters
  • 1988
TLDR
La methode contient des fonctions de probabilites arbitraires qui peuvent etre utilisees par minimiser le temps de relaxation par minimising le tempe de relaxation.
Monte Carlo Sampling Methods Using Markov Chains and Their Applications
SUMMARY A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and
...
1
2
3
4
5
...