## 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 4

We begin with the random walk

most important distributions in physical systems, the Gaussian and Poisson

distributions. Next, we consider the ensemble concept and the ergodic

hypothesis, which ...

We begin with the random walk

**problem**, especially as it relates to two of themost important distributions in physical systems, the Gaussian and Poisson

distributions. Next, we consider the ensemble concept and the ergodic

hypothesis, which ...

Page 145

Second, the analytical properties of free energy and correlations in the Onsager

solution, which laid the groundwork of innumerable future advances that are still

continuing, provided invaluable insights into the

Second, the analytical properties of free energy and correlations in the Onsager

solution, which laid the groundwork of innumerable future advances that are still

continuing, provided invaluable insights into the

**problem**of critical phenomena.Page 257

The central

and to study its dependence on the properties of the potential and the heat bath

to determine universal features, if any. For a review of chemical reaction theory, ...

The central

**problem**of chemical reaction theory is to calculate the reaction rateand to study its dependence on the properties of the potential and the heat bath

to determine universal features, if any. For a review of chemical reaction theory, ...

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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