## 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 36

Page 85

In Chapter 4, liquids are studied by means of the exactly soluble Takahashi

model and other analytical techniques. ... 3.2 BROKEN SYMMETRY AND

CRITICAL PHENOMENA 3.2.1

ideas of this ...

In Chapter 4, liquids are studied by means of the exactly soluble Takahashi

model and other analytical techniques. ... 3.2 BROKEN SYMMETRY AND

CRITICAL PHENOMENA 3.2.1

**Ising Model**: Introduction Almost all the essentialideas of this ...

Page 108

Thus, the same exponent values apply for a planar ferromagnet and the

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

Sometimes intermediate cases arise. For example, consider the following

Hamiltonian ...

Thus, the same exponent values apply for a planar ferromagnet and the

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

**Ising model**.Sometimes intermediate cases arise. For example, consider the following

Hamiltonian ...

Page 161

6.4 EXAMPLE OF METROPOLIS MONTE CARLO 6.4.1 The

method of Metropolis et al. will be applied to the

introduced in Chapter 3. Here, we discuss the two-dimensional lattice, which

exhibits a ...

6.4 EXAMPLE OF METROPOLIS MONTE CARLO 6.4.1 The

**Ising Model**Themethod of Metropolis et al. will be applied to the

**Ising model**, which wasintroduced in Chapter 3. Here, we discuss the two-dimensional lattice, which

exhibits a ...

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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