統(tǒng)計(jì)物理學(xué)中的蒙特卡羅模擬入門(mén)

內(nèi)容概要

本書(shū)是一部詳述了在凝聚態(tài)物理學(xué)、統(tǒng)計(jì)力學(xué)及相關(guān)領(lǐng)域中遇到的復(fù)物理系統(tǒng)蒙特卡羅模擬的各個(gè)方面，書(shū)中各章有應(yīng)用實(shí)例、例題、思考題和習(xí)題，以便于讀者深刻理解書(shū)中所述內(nèi)容。本書(shū)可作為物理學(xué)中的計(jì)算模擬研究生教科書(shū)。

書(shū)籍目錄

Preface1 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 comments3 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  References4 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  References5 More on importance sampling Carlo methods for lattice systms6 Off-lattice models7 Reweighting methods8 Quantum Monte Carlo methods9 Moten Carlo renormalization group methods10 Non-equilibrium and irreversible processes11 Lattice gauge models:brief introduction12 A brief revieew of other methods of computer simulation13 OutlookAppendix:listing of programs mentioned in the text Index

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