## 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 199

where V = dOL/dt is the

center of mass. The relative position vector r = ri — r2 gives a relative

v! — v2. The dynamics of the collision process are best expressed in terms of the

...

where V = dOL/dt is the

**velocity**of the center of mass and R is the position of thecenter of mass. The relative position vector r = ri — r2 gives a relative

**velocity**v =v! — v2. The dynamics of the collision process are best expressed in terms of the

...

Page 221

Initially, the downward

constant force of gravity and decrease owing to the frictional force, which

increases with

and the ...

Initially, the downward

**velocity**of the particle will increase because of theconstant force of gravity and decrease owing to the frictional force, which

increases with

**velocity**. Therefore, after a certain time, the two forces will balance,and the ...

Page 251

The effect of the object on the fluid flow depends on the shape and dimensions of

the object and on the

in Eq. (10.56) becomes large, resulting in turbulent flow. For this reason, we ...

The effect of the object on the fluid flow depends on the shape and dimensions of

the object and on the

**velocity**of the fluid. For large velocities, the nonlinear termin Eq. (10.56) becomes large, resulting in turbulent flow. For this reason, we ...

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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