A guide to monte carlo simulations in statistical physics

Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. This edition now contains material describing powerful new algorithms that have appeared since the previous edition was published, and highlights recent technical advances and key applications that these algorithms now make possible. Updates also include several new sections and a chapter on the use of Monte Carlo simulations of biological molecules. Throughout the book there are many applications, examples, recipes, case studies, and exercises to help the reader understand the material. It is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.

Preface

1 Introduction

2 Some necessary background

3 Simple sampling Monte Carlo methods

4 Importance sampling Monte Carlo methods

5 More on importance sampling Monte Carlo methods of lattice systems

6 Off-lattice models

7 Reweighting methods

8 Quantum Monte Carlo methods

9 Monte Carlo renormalization group methods

10 Non-equilibrium and irreversible processes

11 Lattice gauge models: a brief introduction

12 A brief review of other methods of computer simulation

13 Monte Carlo simulations at the periphery of physics and beyond

14 Monte Carlo studies of biological molecules

15 Outlook

Appendix

Index

Available:*

On Order

Summary

Summary

Table of Contents