## The Monte Carlo method in condensed matter physicsThe "Monte Carlo method" is a method of computer simulation of a system with many degrees of freedom, and thus it has widespread applications in science. It takes its name from the use of random numbers to simulate statistical fluctuations in order to numerically gen- erate probability distributions (which cannot otherwise be known explicitly, since the systems considered are so complex). The Monte Carlo method then yields numerically exact information on "model systems." Such simulations serve two purposes: one can check the extent to which a model system approximates a real system; or one may check the validity of approximations made in analytical theories. This book summarizes recent progress obtained in the implementation of this method and with the general analysis of results, and gives concise reviews of recent applications. These applications include simulations of growth processes far from equilibrium, interfacial phenomena, quantum and classical fluids, polymers, quantum problems on lattices, and random systems. |

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### Contents

Introduction | 1 |

Vectorisation of Monte Carlo Programs for Lattice Models | 23 |

Parallel Algorithms for Statistical Physics Problems | 53 |

Copyright | |

14 other sections not shown

### Common terms and phrases

adsorption algorithm ANNNI model antiferromagnetic approximation atoms Baumgartner behaviour Binder bond boundary conditions calculations Ceperley Chem cluster computer simulations configurations correlation functions critical exponents D.P. Landau density matrix density profiles dielectric diffusion dimensions distribution droplets effects ensemble equation equilibrium estimate Europhys excluded volume experimental fermion ferromagnetic field finite free energy Gaussian GCMC GFMC Green,s function ground-state Hamiltonian hard spheres Hubbard model interactions interface Ising model lattice models layer Lett liquid localised Macromolecules magnetisation MC simulations mixtures molecular dynamics molecules Monte Carlo method Monte Carlo simulations nearest neighbour obtained pair parallel parameter particles percolation phase diagram phase transition Phys Physics PIMC polymer potential Potts model problem processor properties Quantum Monte Carlo random numbers reptation sampling scaling Sect solid spin glass Springer Stat statistical structure surface techniques theory thermodynamic variables variational vector vectorised wall wavefunction wetting zero