Computational Statistical Physics : From Billiards to Monte-Carlo

Hoffmann, Karl-Heinz; Schreiber, Michael

ISBN 10: 3540421602 / ISBN 13: 9783540421603

Editore: Springer, 2001

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Dati bibliografici

• Titolo: Computational Statistical Physics : From Billiards to Monte-Carlo
• Editore: Springer
• Data di pubblicazione: 2001
• Lingua: Inglese
• ISBN 10: 3540421602
• ISBN 13: 9783540421603
• Rilegatura: Rilegato
• Condizione: New

Descrizione articolo

Riassunto

In recent years statistical physics has made significant progress as a result of advances in numerical techniques. While good textbooks exist on the general aspects of statistical physics, the numerical methods and the new developments based on large-scale computing are not usually adequately presented. In this book 16 experts describe the application of methods of statistical physics to various areas in physics such as disordered materials, quasicrystals, semiconductors, and also to other areas beyond physics, such as financial markets, game theory, evolution, and traffic planning, in which statistical physics has recently become significant. In this way the universality of the underlying concepts and methods such as fractals, random matrix theory, time series, neural networks, evolutionary algorithms, becomes clear. The topics are covered by introductory, tutorial presentations.

Dalla quarta di copertina

In recent years statistical physics has made significant progress as a result of advances in numerical techniques. While good textbooks exist on the general aspects of statistical physics, the numerical methods and the new developments based on large-scale computing are not usually adequately presented. In this book 16 experts describe the application of methods of statistical physics to various areas in physics: disordered materials, quasicrystals, semiconductors, ... and also to other areas beyond physics, such as financial markets, game theory, evolution, and traffic planning, in which statistical physics has recently become significant. In this way the universality of the underlying concepts and methods such as fractals, random matrix theory, time series, neural networks, evolutionary algorithms, becomes clear. The topics are covered by introductory, tutorial presentations.