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" Applications of the Monte Carlo Method in Statistical Physics "
edited by Kurt Binder.
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BL
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756566
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b576529
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| Main Entry
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edited by Kurt Binder.
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| Title & Author
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Applications of the Monte Carlo Method in Statistical Physics\ edited by Kurt Binder.
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| Publication Statement
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Berlin, Heidelberg : Springer Berlin Heidelberg, 1984
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| Series Statement
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Topics in current physics, 36.
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(XIV, 311 pages)
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| ISBN
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3642967884
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: 3642967906
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: 9783642967887
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: 9783642967900
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| Contents
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1. A Simple Introduction to Monte Carlo Simulation and Some Specialized Topics --; 1.1 A First Guide to Monte Carlo Sampling --; 1.2 Special Topics --; 1.3 Conclusion --; Appendix. 1.A. Multispin Coding --; References --; Notes Added in Proof --; 2. Recent Developments in the Simulation of Classical Fluids --; 2.1 Some Recent Methodological Developments --; 2.2 Simple Monatomic Fluids --; 2.3 Coulombic Systems --; 2.4 Molecular Liquids --; 2.5 Solutions --; 2.6 Surfaces and Interfaces --; 2.7 Conclusion --; References --; 3. Monte Carlo Studies of Critical and Multicritical Phenomena --; 3.1 Two-Dimensional Lattice-Gas Ising Models --; 3.2 Surfaces and Interfaces --; 3.3 Three-Dimensional Binary-Alloy Ising Models --; 3.4 Potts Models --; 3.5 Continuous Spin Models --; 3.6 Dynamic Critical Behavior --; 3.7 Other Models --; 3.8 Conclusion and Outlook --; References --; 4. Few- and Many-Fermion Problems --; 4.1 Review of the GFMC Method --; 4.2 The Short Time Approximation --; 4.3 The Fermion Problem and the Method of Transient Estimation --; 4.4 The Fixed Node Approximation --; 4.5 An Exact Solution for Few-Fermion Systems --; 4.6 Speculations and Conclusions --; References --; 5. Simulations of Polymer Models --; 5.1 Background --; 5.2 Variants of the Monte Carlo Sampling Techniques --; 5.3 Equilibrium Configurations --; 5.4 Polymer Dynamics --; 5.5 Conclusions and Outlook --; References --; 6. Simulation of Diffusion in Lattice Gases and Related Kinetic Phenomena --; 6.1 General Aspects of Monte Carlo Approaches to Dynamic Phenomena --; 6.2 Diffusion in Lattice-Gas Systems in Equilibrium --; 6.3 Diffusion and Domain Growth in Systems far from Equilibrium --; 6.4 Conclusion --; References --; 7. Roughening and Melting in Two Dimensions --; 7.1 Introductory Remarks --; 7.2 Roughening Transition --; 7.3 Melting Transition --; References --; 8. Monte Carlo Studies of 'Random' Systems --; 8.1 General Introduction --; 8.2 Spin Glasses --; 8.3 Other Systems with Random Interactions --; 8.4 Percolation Theory --; 8.5 Conclusion --; References --; Note Added in Proof --; 9. Monte Carlo Calculations in Lattice Gauge Theories --; 9.1 Lattice Gauge Theories: Fundamental Notions --; 9.2 General Monte Carlo Results for Lattice Gauge Systems --; 9.3 Monte Carlo Determination of Physical Observables --; References --; Additional References with Titles.
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| Abstract
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Monte Carlo computer simulations are now a standard tool in scientific fields such as condensed-matter physics, including surface-physics and applied-physics problems (metallurgy, diffusion, and segregation, etc.), chemical physics, including studies of solutions, chemical reactions, polymer statistics, etc., and field theory. With the increasing ability of this method to deal with quantum-mechanical problems such as quantum spin systems or many-fermion problems, it will become useful for other questions in the fields of elementary-particle and nuclear physics as well. The large number of recent publications dealing either with applications or further development of some aspects of this method is a clear indication that the scientific community has realized the power and versatility of Monte Carlo simula tions, as well as of related simulation techniques such as "molecular dynamics" and "Langevin dynamics," which are only briefly mentioned in the present book. With the increasing availability of recent very-high-speed general-purpose computers, many problems become tractable which have so far escaped satisfactory treatment due to prac tical limitations (too small systems had to be chosen, or too short averaging times had to be used). While this approach is admittedly rather expensive, two cheaper alternatives have become available, too: (i) array or vector processors specifical ly suited for wide classes of simulation purposes; (ii) special purpose processors, which are built for a more specific class of problems or, in the extreme case, for the simulation of one single model system.
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Chemistry.
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Physical organic chemistry.
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Physics.
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| Added Entry
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Kurt Binder
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