Monte Carlo Simulation in Statistical Physics An Introduction

The sixth edition of this highly successful textbook provides a detailed introduction to Monte Carlo simulation in statistical physics, which deals with the computer simulation of many-body systems in condensed matter physics and related fields of physics and beyond (traffic flows, stock market fluc...

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Bibliographic Details
Main Authors: Binder, Kurt, Heermann, Dieter W. (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2019, 2019
Edition:6th ed. 2019
Series:Graduate Texts in Physics
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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300 |a XVII, 258 p. 155 illus., 5 illus. in color  |b online resource 
505 0 |a Introduction: Purpose and Scope of this Volume, and Some General Comments -- Theoretical Foundations of the Monte Carlo Method and Its Applications in Statistical Physics -- Guide to Practical Work with the Monte Carlo Method -- Some Important Developments of the Monte Carlo Methodology -- Quantum Monte Carlo Simulation: An Introduction -- Monte Carlo Methods for the Sampling of Free Energy Landscapes -- Special Monte Carlo Algorithms -- Finite Size Scaling Tools for the Study of Interfacial Phenomena and Wetting 
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653 |a Physical Chemistry 
653 |a Mathematical Physics 
653 |a System theory 
653 |a Mathematical physics 
653 |a Theoretical, Mathematical and Computational Physics 
653 |a Condensed matter 
700 1 |a Heermann, Dieter W.  |e [author] 
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520 |a The sixth edition of this highly successful textbook provides a detailed introduction to Monte Carlo simulation in statistical physics, which deals with the computer simulation of many-body systems in condensed matter physics and related fields of physics and beyond (traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, these powerful simulation methods calculate probability distributions, making it possible to estimate the thermodynamic properties of various systems. The book describes the theoretical background of these methods, enabling newcomers to perform such simulations and to analyse their results. It features a modular structure, with two chapters providing a basic pedagogic introduction plus exercises suitable for university courses; the remaining chapters cover major recent developments in the field. This edition has been updated with two new chapters dealing with recently developed powerful special algorithms and with finitesize scaling tools for the study of interfacial phenomena, which are important for nanoscience. Previous editions have been highly praised and widely used by both students and advanced researchers