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统计物理学中的蒙特卡罗模拟入门（英文版）

统计物理学中的蒙特卡罗模拟入门（英文版）

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作者: D.P.Landau 著 , K.Binder 著

出版社: 世界图书出版公司

出版时间: 2004-04

版次: 1

ISBN: 9787506265713

定价: 89.00

装帧: 平装

开本: 其他

纸张: 胶版纸

页数: 384页

分类: 自然科学

12人买过

本书是一部详述了在凝聚态物理学、统计力学及相关领域中遇到的复物理系统蒙特卡罗模拟的各个方面，书中各章有应用实例、例题、思考题和习题，以便于读者深刻理解书中所述内容。本书可作为物理学中的计算模拟研究生教科书。 Preface

1 Introduction

  1.1 What is a Monte Carlo simulation?

  1.2 What porblems can we solve with it?

  1.3 What difficulties will we encounter?

  1.4 What strategr Should we follow in approaching a problem?

  1.5 How do simulations relate to theory and experiment?

2 Some necessary background

  2.1 Thermodynamics and statistical mechanics:a quick reminder

  2.2 Probability theory

  2.3 Non-equilirium and dynamics:some introductory comments

3 Simple sampling Monte Carol methods

  3.1 Introduction

  3.2 Comparisons of methods for numerical integration of given functions

  3.3 Boundary value problems

  3.4 Simulation of radionactive decay

  3.5 Simulation of transport properties

  3.6 The Percolation Problem

  3.7 Finding the guoundstate of a Hamiltonian

  3.8 Generation of ‘random’walks

  3.9 Final remarks

  References

4 Importance sampling Monte Carlo methods

  4.1 Introduction

  4.2 The simplest case:single spin-flip sampling for the simple Ising model

  4.3 Other discrete variable models

  4.4 Spin-exchange sampling

  4.5 Microcanonical methods

  4.6 General remarks,choice of ensemble

  4.7 Statics and dynamics of polymer models on lattices

  4.8 Some advice

  References

5 More on importance sampling Carlo methods for lattice systms

6 Off-lattice models

7 Reweighting methods

8 Quantum Monte Carlo methods

9 Moten Carlo renormalization group methods

10 Non-equilibrium and irreversible processes

11 Lattice gauge models:brief introduction

12 A brief revieew of other methods of computer simulation

13 Outlook

Appendix:listing of programs mentioned in the text

Index
内容简介:
本书是一部详述了在凝聚态物理学、统计力学及相关领域中遇到的复物理系统蒙特卡罗模拟的各个方面，书中各章有应用实例、例题、思考题和习题，以便于读者深刻理解书中所述内容。本书可作为物理学中的计算模拟研究生教科书。
目录:
Preface

1 Introduction

  1.1 What is a Monte Carlo simulation?

  1.2 What porblems can we solve with it?

  1.3 What difficulties will we encounter?

  1.4 What strategr Should we follow in approaching a problem?

  1.5 How do simulations relate to theory and experiment?

2 Some necessary background

  2.1 Thermodynamics and statistical mechanics:a quick reminder

  2.2 Probability theory

  2.3 Non-equilirium and dynamics:some introductory comments

3 Simple sampling Monte Carol methods

  3.1 Introduction

  3.2 Comparisons of methods for numerical integration of given functions

  3.3 Boundary value problems

  3.4 Simulation of radionactive decay

  3.5 Simulation of transport properties

  3.6 The Percolation Problem

  3.7 Finding the guoundstate of a Hamiltonian

  3.8 Generation of ‘random’walks

  3.9 Final remarks

  References

4 Importance sampling Monte Carlo methods

  4.1 Introduction

  4.2 The simplest case:single spin-flip sampling for the simple Ising model

  4.3 Other discrete variable models

  4.4 Spin-exchange sampling

  4.5 Microcanonical methods

  4.6 General remarks,choice of ensemble

  4.7 Statics and dynamics of polymer models on lattices

  4.8 Some advice

  References

5 More on importance sampling Carlo methods for lattice systms

6 Off-lattice models

7 Reweighting methods

8 Quantum Monte Carlo methods

9 Moten Carlo renormalization group methods

10 Non-equilibrium and irreversible processes

11 Lattice gauge models:brief introduction

12 A brief revieew of other methods of computer simulation

13 Outlook

Appendix:listing of programs mentioned in the text

Index

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