## 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. |

### From inside the book

Results 1-3 of 88

Page 14

1.3.2 Moments of Random Variables We consider a random variable X that takes

exactly the same as the kth moment of the probability distribution. The same is ...

1.3.2 Moments of Random Variables We consider a random variable X that takes

**values**x, with probability distribution P(xi). The &th moment of the variable X isexactly the same as the kth moment of the probability distribution. The same is ...

Page 108

The

given

and the superfluid transition in helium, but they are different from those of the

Ising ...

The

**values**of the exponents are dependent on n, but they are the same for agiven

**value**of n. Thus, the same exponent**values**apply for a planar ferromagnetand the superfluid transition in helium, but they are different from those of the

Ising ...

Page 332

For the von Neumann neighborhood, each cell evolves either according to the

neighbors. For the Moore neighborhood, each cell evolves either according to

the ...

For the von Neumann neighborhood, each cell evolves either according to the

**values**of its four neighbors or according to its**value**and the**values**of its fourneighbors. For the Moore neighborhood, each cell evolves either according to

the ...

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### 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