## Statistical mechanics: fundamentals and modern applicationsThis book examines the latest developments in statistical mechanics, a branch of physical chemistry and physics that uses statistical techniques to predict the properties and the behavior of chemical and physical systems. It begins with a review of some of the essential concepts and then discusses recent developments in both equilibrium and nonequilibrium statistical mechanics. It covers liquids, phase transitions, renormalization theory, Monte Carlo techniques, and chaos. |

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Page ix

1

Equilibrium, 206 8.5 Transport Properties, 208 8.5.1 Hydrodynamic Equations of

Change, 208 8.5.2 Transport Equations, 209 8.6 Concluding Remarks, 210 8.7 ...

1

**Derivation**of Boltzmann Equation, 202 8.4.2 Collision Term, 203 8.4.3Equilibrium, 206 8.5 Transport Properties, 208 8.5.1 Hydrodynamic Equations of

Change, 208 8.5.2 Transport Equations, 209 8.6 Concluding Remarks, 210 8.7 ...

Page 198

This latter

of distribution functions called the BBGKY hierarchy for Bogoliubov, Born, Green,

Kirkwood, and Yvon (BBGKY). For details of the

This latter

**derivation**, which is beyond the scope of this book, leads to a hierarchyof distribution functions called the BBGKY hierarchy for Bogoliubov, Born, Green,

Kirkwood, and Yvon (BBGKY). For details of the

**derivation**using the BBGKY ...Page 202

117) the relation between the cross-section for scattering in laboratory

coordinates <r(x) and in the center-of-mass system a(&) is <r(X) = cr(Š) sinŠ sin*

dŽ dx (8.14) 8.4 BOLTZMANN EQUATION 8.4.1

Equation For the ...

117) the relation between the cross-section for scattering in laboratory

coordinates <r(x) and in the center-of-mass system a(&) is <r(X) = cr(Š) sinŠ sin*

dŽ dx (8.14) 8.4 BOLTZMANN EQUATION 8.4.1

**Derivation**of BoltzmannEquation For the ...

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### Contents

Classical Statistical Mechanics | 3 |

Quantum Statistical Mechanics | 45 |

Phase Transitions and Critical Phenomena | 83 |

Copyright | |

14 other sections not shown

### Common terms and phrases

attractor automata average behavior bifurcation Boltzmann Boltzmann equation Brownian motion Brownian particle BZ reaction calculate called canonical ensemble cell cellular automaton chaos Chapter coefficient collisions configuration consider coordinates correlation functions coupling constants critical exponents critical point defined depends derivation dimension discussed distribution function dynamics eigenvalues entropy equilibrium evaluated example ferromagnetic fixed point fluctuations fluid FORTRAN FORTRAN program fractal free energy frequency Gaussian Hamiltonian initial integral interactions Ising model iterations Kramers Langevin equation lattice limit cycle linear magnetization Markovian matrix method microcanonical ensemble microstates molecular nonequilibrium nonlinear number of particles obtained one-dimensional order parameter oscillations partition function Pathria phase space phase transition polymer potential power spectrum probability density problem protein quantities quantum mechanics RANDOM NUMBER random walk scaling Section shown in Figure simulation solution spin glass statistical mechanics steps stochastic temperature theorem thermodynamic limit total number values vector velocity zero