This book deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics as well as in related fields, for example polymer science and lattice gauge theory. After briefly recalling essential background in statistical mechanics and probability theory, the authors give a succinct overview of simple sampling methods. The next several chapters develop the importance sampling method. The concepts behind the various simulation algorithms are explained. The fact that simulations deal with small systems is emphasized. Other chapters also provide introductions to quantum Monte Carlo methods, aspects of simulations of growth phenomena and other systems far from equilibrium, and the Monte Carlo Renormalization Group approach to critical phenomena. Throughout the book there are many applications, examples, and exercises to help the reader in a thorough study of this book; furthermore, up-to-date references to more specialized literature are also provided.
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Book Description
Editorial Reviews
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'... the most complete book on Monte Carlo simulations that I have ever read, written by two of the field's most well-respected authorities. The book contains a detailed description of the different methods and techniques illustrated with clear and concrete examples, making it an invaluable reference of anyone - from novices to experts - interested in Monte Carlo simulations. ... The book's presentation is exceptionally clear, making for entertaining reading without sacrificing mathematical rigor. ... the book is invaluable for its detailed presentations of finite size effects, ergodicity, critical slowing down, and the difficulties involved in off-lattice methods, to name just a few example topics. ... In recent years, my research interests have made extensive use of molecular dynamics simulations, but reading this book has inspired several applications that will make use of Monte Carlo Methods. I'm sure this inspiration will pass on to anyone else reading this book.' Computing in Science and Engineering
Book Description
This book deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics as well as in related fields, for example polymer science and lattice gauge theory. It includes many applications, examples, and exercises throughout.
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11 of 11 people found the following review helpful:
1.0 out of 5 stars
Merely a collection of paper abstracts, hardly a "guide",
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This review is from: A Guide to Monte Carlo Simulations in Statistical Physics (Hardcover)
I agree that it covers a lot of topics, many of them are important. They actually include much more topics in the second edition than the first one. However, the authors seldomly discuss one topic more than a page. It's like reading abstracts of papers. So if you already know the stuff, you don't need this book. Just go for some papers (papers are at least up to date). If you don't know anything about Monte Carlo sampling, this book is not going to help you too much. So don't waste your money on this book. Newman's book or Frenkel's book is much better.
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Inside This Book
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First Sentence:
In a Monte Carlo simulation we attempt to follow the 'time dependence' of a model for which change, or growth, does not proceed in some rigorously predefined fashion (e.g. according to Newton's equations of motion) but rather in a stochastic manner which depends on a sequence of random numbers which is generated during the simulation. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
dynamic finite size scaling, checkerboard decomposition, lattice gauge models, occupied vertices, finite size behavior, single sublattice, flipping probabilities, different random number sequences, flipping methods, critical relaxation, excluded volume constraint, bond fluctuation model, deconfinement transition, finite size scaling analysis, different lattice sizes, effective monomers, tricritical point, monomer positions, multicritical point, thermodynamic derivatives, topological excitations, fourth order cumulant, finite size effects, trial move, mean cluster size Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Lennard Jones, New York, Academic Press, World Scientific, Computer Simulation Studies, Oxford University Press, Zinn Justin, Cambridge University Press, Cornell University Press, Springer Verlag, Cambridge Philos, Computer Phys, Computer Simulations Studies, Hubbard Hamiltonian, San Miguel, Societa Italiana New!
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In a Monte Carlo simulation we attempt to follow the 'time dependence' of a model for which change, or growth, does not proceed in some rigorously predefined fashion (e.g. according to Newton's equations of motion) but rather in a stochastic manner which depends on a sequence of random numbers which is generated during the simulation. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
dynamic finite size scaling, checkerboard decomposition, lattice gauge models, occupied vertices, finite size behavior, single sublattice, flipping probabilities, different random number sequences, flipping methods, critical relaxation, excluded volume constraint, bond fluctuation model, deconfinement transition, finite size scaling analysis, different lattice sizes, effective monomers, tricritical point, monomer positions, multicritical point, thermodynamic derivatives, topological excitations, fourth order cumulant, finite size effects, trial move, mean cluster size Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Lennard Jones, New York, Academic Press, World Scientific, Computer Simulation Studies, Oxford University Press, Zinn Justin, Cambridge University Press, Cornell University Press, Springer Verlag, Cambridge Philos, Computer Phys, Computer Simulations Studies, Hubbard Hamiltonian, San Miguel, Societa Italiana New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 34
books:
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31
books
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- Index, Volume 20 (Phase Transitions and Critical Phenomena) by Cyril Domb on 7 pages
- Statistical Physics, Third Edition, Part 1: Volume 5 (Course of Theoretical Physics, Volume 5) by L D Landau on 6 pages
- The Monte Carlo Method in Condensed Matter Physics (Topics in Applied Physics) by K. Binder on 5 pages
- Scaling Concepts in Polymer Physics by Pierre Gilles De Gennes on page 66, page 131, and page 227
- Quantum Mechanics and Path Integrals by Richard P. Feynman on page 284, and page 330
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- Computer Simulation Studies in Condensed-Matter Physics XVII: Proceedings of the Seventeenth Workshop, Athens, GA, USA, February 16-20, 2004 (Springer Proceedings in Physics) (v. 17) by David P. Landau on 4 pages
- Parallel Programming in C with MPI and OpenMP by Michael Quinn on page 269, and Back Matter
- Phase Transitions in Combinatorial Optimization Problems: Basics, Algorithms and Statistical Mechanics by Alexander K. Hartmann on page 168, and page 325
- Computational Materials Chemistry: Methods and Applications (Bioelectric Engineering) by L.A. Curtiss on page 121
- Monte Carlo Simulation in Statistical Physics by Kurt Binder in Back Matter
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