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平衡态统计物理学 第3版 影印版 英文

平衡态统计物理学 第3版 影印版 英文

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内容简介
平衡态统计物理学 第3版 影印版 英文
出版时间:2010
内容简介
  During the last decade each of the authors has regularly taught a graduate or senior undergraduate course in statistical mechanics. During this same period, the renormalization group approach to critical phenomena, pioneered by K. G. Wilson, greatly altered our approach to condensed matter physics. Since its introduction in the context of phase transitions, the method has found application in many other areas of physics, such as many-body theory, chaos, the conductivity of disordered materials, and fractal structures. So pervasive is its influence that we feel that it now essential that graduate students be introduced at an early stage in their career to the concepts of scaling,
目录
Preface to the First Edition
Preface to the Second Edition
Preface to the Third Edition
1 Review of Thermodynamics
 1.1 State Variables and Equations of State
 1.2 Laws of Thermodynamics
  1.2.1 First law
  1.2.2 Second law
 1.3 Thermodynamic Potentials
 1.4 Gibbs-Duhem and Maxwell Relations
 1.5 Response Functions
 1.6 Conditions for Equilibrium and Stability
 1.7 Magnetic Work
 1.8 Thermodynamics of Phase Transitions
 1.9 Problems
2 Statistical Ensembles
 2.1 Isolated Systems: Microcanonical Ensemble
 2.2 Systems at Fixed Temperature: Canonical Ensemble
 2.3 Grand Canonical Ensemble
 2.4 Quantum Statistics
  2.4.1 Harmonic oscillator
  2.4.2 Noninteracting fermions
  2.4.3 Noninteracting bosons
  2.4.4 Density matrix
 2.5 Maximum Entropy Principle
 2.6 Thermodynamic Variational Principles .
  2.6.1 Schottky defects in a crystal
 2.7 Problems
3 Mean Field and Landau Theory
 3.1 Mean Field Theory of the Ising Model
 3.2 Bragg-Williams Approximation
 3.3 A Word of Warning
 3.4 Bethe Approximation
 3.5 Critical Behavior of Mean Field Theories
 3.6 Ising Chain: Exact Solution
 3.7 Landau Theory of Phase Transitions
 3.8 Symmetry Considerations
  3.8.1 Potts model
 3.9 Landau Theory of Tricritical Points
 3.10 Landau-Ginzburg Theory for Fluctuations
 3.11 Multicomponent Order Parameters: n-Vector Model
 3.12 Problems
4 Applications of Mean Field Theory
 4.1 Order-Disorder Transition
 4.2 Maier-Sanpe Model
 4.3 Blume——Emery-Grifliths Model
 4.4 Mean Field Theory of Fluids: van der Waals Approach
 4.5 Spruce Budworm Model
 4.6 A Non-Equilibrium System: Two Species Asymmetric Exclusion Model
 4.7 Problems
5 Dense Gases and Liquids
 5.1Virial Expansion
 5.2 Distribution Functions
  5.2.1 Pair correlation function
  5.2.2 BBGKY hierarchy
  5.2.3 Ornstein-Zernike equation
 5.3 Perturbation Theory
 5.4 Inhomogeneous Liquids
  5.4.1 Liquid-vapor interface
  5.4.2 Capillary waves
 5.5 Density-Functional Theory
  5.5.1 Functional differentiation
  5.5.2 Free-energy functionals and correlation functions
  5.5.3 Applications
 5.6 Problems
6 Critical Phenomena I
 6.1 Ising Model in Two Dimensions
  6.1.1 Transfer matrix
  6.1.2 Transformation to an interacting fermion problem
  6.1.3 Calculation of eigenvalues
  6.1.4 Thermodynamic functions
  6.1.5 Concluding remarks
 6.2 Series Expansions
  6.2.1 High-temperature expansions
  6.2.2 Low-temperature expansions
  6.2.3 Analysis of series
 6.3 Scaling
  6.3.1 Thermodynamic considerations
  6.3.2 Scaling hypothesis
  6.3.3 Kadanoff block spins
 6.4 Finite-Size Scaling
 6.5 Universality
 6.6 Kosterlitz-Thouless Transition
 6.7 Problems
7 Critical Phenomena II: The Renormalization Group
 7.1 The Ising Chain Revisited
 7.2 Fixed Points
 7.3 An Exactly Solvable Model: Ising Spins on a Diamond Fractal
 7.4 Position Space Renormalization: Cumulant Method
  7.4.1 First-order approximation
  7.4.2 Second-order approximation
 7.5 Other Position Space Renormalization Group Methods
  7.5.1 Finite lattice methods
  7.5.2 Adsorbed monolayers: Ising antiferromagnet
  7.5.3 Monte Carlo renormalization
 7.6 Phenomen01ogical Renormalization Group
 7.7 The e-Expansion
  7.7.1 The Gaussian model
  7.7.2 The S4 model
  7.7.3 Conclusion
 Appendix: Second Order Cumulant Expansion
 7.8 Problems
8 Stochastic Processes
 8.1 Markov Processes and the Master Equation
 8.2 Birth and Death Processes
 8.3 Branching Processes
 8.4 Fokker-Planck Equation
 8.5 Fokker-Planck Equation with Several Variables: SIR Model
 8.6 Jump Moments for Continuous Variables
  8.6.1 Brownian motion
  8.6.2 Rayleigh and Kramers equations
 8.7 Diffusion, First Passage and Escape
  8.7.1 Natural boundaries: The Kimura-Weiss model for genetic drift
  8.7.2 Artificial boundaries
  8.7.3 First passage time and escape probability
  8.7.4 Kramers escape rate
 8.8 Transformations of the Fokker-Planck Equation
  8.8.1 Heterogeneous diffusion
  8.8.2 Transformation to the SchrSdinger equation
  8.9 Problems
9 Simulations
 9.1 Molecular Dynamics
  9.1.1 Conservative molecular dynamics
  9.1.2 Brownian dynamics
  9.1.3 Data analysis
 9.2 Monte Carlo Method
  9.2.1 Discrete time Markov processes
  9.2.2 Detailed balance and the Metropolis algorithm
  9.2.3 Histogram methods
 9.3 Data Analysis
  9.3.1 Fluctuations
 ……
10 Polymers and Membranes
11 Quantum Fluids
12 Linear Response Theory
13 Disordered Systems