## 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 42

Page 148

Next, we must decide on the

the final equilibrium state is independent of the

principle, we first position the particles randomly in the box. To conserve

computer ...

Next, we must decide on the

**initial**positions and velocities of the particles. Sincethe final equilibrium state is independent of the

**initial**conditions, at least inprinciple, we first position the particles randomly in the box. To conserve

computer ...

Page 313

V; 05 12.5.5 Universality in Chaos In a deterministic system, because of

sensitivity to

That is the phenomenon of chaos. In principle, the deterministic system is totally

predictable ...

V; 05 12.5.5 Universality in Chaos In a deterministic system, because of

sensitivity to

**initial**conditions, unpredictable behavior at long times may arise.That is the phenomenon of chaos. In principle, the deterministic system is totally

predictable ...

Page 328

In fact, except for an

eventually goes to a period 2 cycle. The period 2 cycle is the attractor for cellular

automaton 50. Cellular automaton 1 26 (0 1 1 1 1 1 1 0), a Class 3 cellular ...

In fact, except for an

**initial**configuration of all 1 's or all 0's, cellular automaton 50eventually goes to a period 2 cycle. The period 2 cycle is the attractor for cellular

automaton 50. Cellular automaton 1 26 (0 1 1 1 1 1 1 0), a Class 3 cellular ...

### 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