## 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 31

Page 270

In the presence of coupling, both of these will be changed to new

which are given by the eigenvalues of the matrix V. The coordinates of the

particles, bath, and the system are uncoupled for zero coupling but are coupled

when c\ ...

In the presence of coupling, both of these will be changed to new

**frequencies**,which are given by the eigenvalues of the matrix V. The coordinates of the

particles, bath, and the system are uncoupled for zero coupling but are coupled

when c\ ...

Page 302

0.0 2.0 4.0 6.0

series in Figure 1 2.5(a). of the power spectra is close to the average

V& of the peaks in the time series, which is 0.13978. Another advantage of using

...

0.0 2.0 4.0 6.0

**Frequency**Figure 12.8 A portion of the power spectrum of the timeseries in Figure 1 2.5(a). of the power spectra is close to the average

**frequency**V& of the peaks in the time series, which is 0.13978. Another advantage of using

...

Page 396

Gauss's divergence theorem, 35 Gaussian distribution, 8-10 and polymers, 252

and white noise, 226 Generalized coordinates, 16 Geometric series, 61, 72 GH

...

Gauss's divergence theorem, 35 Gaussian distribution, 8-10 and polymers, 252

and white noise, 226 Generalized coordinates, 16 Geometric series, 61, 72 GH

**frequency**, see Grote-Hynes**frequency**GH rate coefficient, see Grote-Hynes rate...

### 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