Computer Simulation Methods in Theoretical Physics / Edition 2

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Computational methods pertaining to many branches of science, such as physics, physical chemistry and biology, are presented. The text is primarily intended for third-year undergraduate or first-year graduate students. However, active researchers wanting to learn about the new techniques of computational science should also benefit from reading the book. It treats all major methods, including the powerful molecular dynamics method, Brownian dynamics and the Monte-Carlo method. All methods are treated equally from a theroetical point of view. In each case the underlying theory is presented and then practical algorithms are displayed, giving the reader the opportunity to apply these methods directly. For this purpose exercises are included. The book also features complete program listings ready for application.

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Editorial Reviews

A slim little text designed to acquaint advanced undergraduate and beginning graduate students of physics (knowledge of classical mechanics, statistical mechanics and computer programming is assumed) with the art and excitement of the topic to which the title refers. Four chapters (Introductory examples, Computer-simulation methods, Deterministic methods, Stochastic methods) provide the student with what is in effect a computer-lab workbook, an invitation to learn "hands-on" some exciting things both about applied computation and about physics. An appendix provides information about random number generators, and there is a useful bibliography. (NW) Annotation c. Book News, Inc., Portland, OR (
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Product Details

  • ISBN-13: 9783540522102
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 1/1/1995
  • Edition description: 2nd ed.
  • Edition number: 2
  • Pages: 145

Table of Contents

1. Introductory Examples.- 1.1 Percolation.- 1.2 A One-Particle Problem.- Problems.- 2. Computer-Simulation Methods.- Problems.- 3. Deterministic Methods.- 3.1 Molecular Dynamics.- Integration Schemes.- Calculating Thermodynamic Quantities.- Organization of a Simulation.- 3.1.1 Microcanonical Ensemble Molecular Dynamics.- 3.1.2 Canonical Ensemble Molecular Dynamics.- 3.1.3 Isothermal-Isobaric Ensemble Molecular Dynamics.- Problems.- 4. Shastic Methods.- 4.1 Preliminaries.- 4.2 Brownian Dynamics.- 4.3 Monte-Carlo Method.- 4.3.1 Microcanonical Ensemble Monte-Carlo Method.- 4.3.2 Canonical Ensemble Monte-Carlo Method.- 4.3.3 Isothermal-Isobaric Ensemble Monte-Carlo Method.- 4.3.4 Grand Ensemble Monte-Carlo Method.- Problems.- A 1. Random Number Generators.- A2. Program Listings.- References.

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