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书名 从马尔科夫链到非平衡粒子系统(第2版)
分类 科学技术-自然科学-数学
作者 陈木法
出版社 世界图书出版公司
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简介
目录

Preface to the First Edition

Preface to the Second Edition

Chapter 0. An Overview of the Book: Starting From Markov Chains

 0.1. Three Classical Problems for Markov Chains

 0.2. Probability Metrics and Coupling Methods

 0.3. Reversible Markov Chains

 0.4. Large Deviations and Spectral Gap

 0.5. Equilibrium Particle Systems

 0.6. Non-equilibrium Particle Systems

Part I. General Jump Processes

Chapter 1. Transition Function and its Laplace Transform

 1.1. Basic Properties of Transition Function

 1.2. The q-Pair

 1.3. Differentiability

 1.4. Laplace Transforms

 1.5. Appendix

 1.6. Notes

Chapter 2. Existence and Simple Constructions of Jump Processes

 2.1. Minimal Nonnegative Solutions

 2.2. Kolmogorov Equations and Minimal Jump Process

 2.3. Some Sufficient Conditions for Uniqueness

 2.4. Kolmogorov Equations and q-Condition

 2.5. Entrance Space and Exit Space

 2.6. Construction of q-Processes with Single-Exit q-Pair

 2.7. Notes

Chapter 3. Uniqueness Criteria

 3.1. Uniqueness Criteria Based on Kolmogorov Equations

 3.2. Uniqueness Criterion and Applications

 3.3. Some Lemmas

 3.4. Proof of Uniqueness Criterion

 3.5. Notes

Chapter 4. Recurrence, Ergodicity and Invariant Measures

 4.1. Weak Convergence

 4.2. General Results

 4.3. Markov Chains: Time-discrete Case

 4.4. Markov Chains: Time-continuous Case

 4.5. Single Birth Processes

 4.6. Invariant Measures

 4.7. Notes

Chapter 5. Probability Metrics and Coupling Methods

 5.1. Minimum LP-Metric

 5.2. Marginality and Regularity

 5.3. Successful Coupling and Ergodicity

 5.4. Optimal Markovian Couplings

 5.5. Monotonicity

 5.6. Examples

 5.7. Notes

Part II. Symmetrizable Jump Processes

Chapter 6. Symmetrizable Jump Processes and Dirichlet Forms

 6.1. Reversible Markov Processes

 6.2. Existence

 6.3. Equivalence of Backward and Forward Kolmogorov Equations

 6.4. General Representation of Jump Processes

 6.5. Existence of Honest Reversible Jump Processes

 6.6. Uniqueness Criteria

 6.7. Basic Dirichlet Form

 6.8. Regularity, Extension and Uniqueness

 6.9. Notes

Chapter 7. Field Theory

 7.1. Field Theory

 7.2. Lattice Field

 7.3. Electric Field

 7.4. Transience of Symmetrizable Markov Chains

 7.5. Random Walk on Lattice Fractals

 7.6. A Comparison Theorem

 7.7. Notes

Chapter 8. Large Deviations

 8.1. Introduction to Large Deviations

 8.2. Rate Function

 8.3. Upper Estimates

 8.4. Notes

Chapter 9. Spectral Gap

 9.1. General Case: an Equivalence

 9.2. Coupling and Distance Method

 9.3. Birth-Death Processes

 9.4. Splitting Procedure and Existence Criterion

 9.5. Cheeger's Approach and Isoperimetric Constants

 9.6. Notes

Part III. Equilibrium Particle Systems

Chapter 10. Random Fields

 10.1. Introduction

 10.2. Existence

 10.3. Uniqueness

 10.4. Phase Transition: Peierls Method

 10.5. Ising Model on Lattice Fractals

 10.6. Reflection Positivity and Phase Transitions

 10.7. Proof of the Chess-Board Estimates

 10.8. Notes

Chapter 11. Reversible Spin Processes and Exclusion Processes

 11.1. Potentiality for Some Speed Functions

 11.2. Constructions of Gibbs States

 11.3. Criteria for Reversibility

 11.4. Notes

Chapter 12. Yang-Mills Lattice Field

 12.1. Background

 12.2. Spin Processes from Yang-Mills Lattice Fields

 12.3. Diffusion Processes from Yang-Mills Lattice Fields

 12.4. Notes

Part IV. Non-equilibrium Particle Systems

Chapter 13. Constructions of the Processes

 13.1. Existence Theorems for the Processes

 13.2. Existence Theorem for Reaction-Diffusion Processes

 13.3. Uniqueness Theorems for the Processes

 13.4. Examples

 13.5. Appendix

 13.6. Notes

Chapter 14. Existence of Stationary Distributions and Ergodicity

 14.1. General Results

 14.2. Ergodicity for Polynomial Model

 14.3. Reversible Reaction-Diffusion Processes

 14.4. Notes

Chapter 15. Phase Transitions

 15.1. Duality

 15.2. Linear Growth Model

 15.3. Reaction-Diffusion Processes with Absorbing State

 15.4. Mean Field Method

 15.5. Notes

Chapter 16. Hydrodynamic Limits

 16.1. Introduction: Main Results

 16.2. Preliminaries

 16.3. Proof of Theorem 16.1

 16.4. Proof of Theorem 16.3

 16.5. Notes

Bibliography

Author Index

Subject Index

编辑推荐

《从马尔科夫链到非平衡粒子系统(第2版)》作者陈木法先生是北京师范大学教授,中科院院士。作者最先从非平衡统计物理中引进无穷维反应扩散过程,解决了过程的构造、平衡态的存在性和唯一性等根本课题,此方向今已成为国际上粒子系统研究的重要分支。本书主要阐述概率论及其在物理学中的应用,全书分为4部分,16章。本书可作为随机过程课程研究生教材。

内容推荐
本书主要阐述概率论及其在物理学中的应用, 全书分为4部分, 16章。作者陈木法是北京师范大学教授, 中科院院士。
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