Ten lectures on random media随机媒介讲座
点此进入淘宝搜索页搜索分类: 图书,进口原版书,科学与技术 Science & Techology ,
作者： Erwin Bolthausen 著
出 版 社：
出版时间： 2002-3-1字数：版次： 1页数： 116印刷时间： 2002/03/01开本： 16开印次： 1纸张： 胶版纸I S B N ： 9783764367039包装： 平装内容简介
The field of random media has been the object of intensive activity over the last twenty-five years. It gathers a variety of models generally originating from physical sciences, where certain materials or substances have defects or inhomogeneities. This feature can be taken into account by letting the medium be random. Randomness in the medium turns out to cause very unexpected effects, especially in the large-scale behavior of some of these models. What in the beginning was often deemed to be a simple toy-model ended up as a major mathematical challenge. After more than twenty years of intensive research in this field, certain new paradigms and some general methods have emerged, and the surprising results on the asymptotic behavior of individual models are now better understood in more general frameworks. This monograph grew out of the DMV Lectures on Random Media held by the authors at the Mathematical Research Institute in Oberwolfach in November 1999 and tries to give an account of some of the developments in the field, especially in the area of random motions in random media and of mean-field spin glasses. It will be a valuable resource for postgraduates and researchers in probability theory and mathematical physics.
目录
Contents
PART ONE: Lectures on Random Motions in Random Media
Foreword
A Brief Introduction
Lecture 1: The Environment Viewed from the Particle
Lecture 2: Central Limit Theorem for Random Walks in Random Environment with Null Drift
Lecture 3: Long Time Survival among Random Traps
Lecture 4: Multi-dimensional Random Walks in Random Environment
Lecture 5: More on Random Walks in Random Environment
PART TWO: Lectures on Spin Glasses
Lecture 6: On the Sherrington-Kirkpatrick Model of Spin Glasses
Lecture 7: The Sherrington-Kirkpatrick Model: High Temperature and Nonzero Magnetic Field
Lecture 8: The Random Energy Model
Lecture 9: The Generalized Random Energy Model and Induced Clusterings
Lecture 10: Markovian Clustering, Reshuffling, and a Self-consistency Equation
References
Index