## A Guide to Monte Carlo Simulations in Statistical PhysicsThis new and updated edition deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics, statistical mechanics, and related fields. After briefly recalling essential background in statistical mechanics and probability theory, it gives a succinct overview of simple sampling methods. The concepts behind the simulation algorithms are explained comprehensively, as are the techniques for efficient evaluation of system configurations generated by simulation. It contains many applications, examples, and exercises to help the reader and provides many new references to more specialized literature. This edition includes a brief overview of other methods of computer simulation and an outlook for the use of Monte Carlo simulations in disciplines beyond physics. This is an excellent guide for graduate students and researchers who use computer simulations in their research. It can be used as a textbook for graduate courses on computer simulations in physics and related disciplines. |

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### Contents

Some necessary background | 7 |

Simple sampling Monte Carlo methods | 48 |

Importance sampling Monte Carlo methods | 68 |

More on importance sampling Monte Carlo methods | 137 |

Offlattice models | 194 |

Reweighting methods | 251 |

Quantum Monte Carlo methods | 277 |

Monte Carlo renormalization group methods | 315 |

### Other editions - View all

A Guide to Monte Carlo Simulations in Statistical Physics David P. Landau,Kurt Binder Limited preview - 2014 |

A Guide to Monte Carlo Simulations in Statistical Physics David P. Landau,Kurt Binder Limited preview - 2014 |

A Guide to Monte Carlo Simulations in Statistical Physics David P. Landau,Kurt Binder Limited preview - 2000 |

### Common terms and phrases

algorithm antiferromagnet applied approach atoms average behavior Binder bond calculated chain Chapter Chem chemical potential classical cluster configuration consider correlation critical exponents critical point degrees of freedom density described determine dimensions distribution endif equation equilibrium error estimate example ferromagnet field finite size effects finite size scaling flipping fluctuations fluid free energy groundstate Hamiltonian Heisenberg histogram integration interactions interface internal energy Ising model Ising square lattice kinetic Landau length Lett linear magnetization Metropolis molecular dynamics monomers Monte Carlo methods Monte Carlo simulations nearest neighbor obtained order parameter order transition particles partition function percolation periodic boundary conditions phase transition Phys physics polymer Potts model probability problem properties quantities quantum random number random walk randomly relaxation renormalization sampling shown in Fig simple space specific heat spin glass square lattice statistical mechanics surface techniques theory thermodynamic tion tricritical point two-dimensional variables vector zero