Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics

Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics PDF Author: Raymond E. Alcouffe
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 508

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Book Description

Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics

Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics PDF Author: Raymond E. Alcouffe
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 508

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Book Description


Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics

Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics PDF Author: Raymond Alcouffe
Publisher:
ISBN:
Category :
Languages : en
Pages : 483

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Book Description


Monte Carlo Methods in Statistical Physics

Monte Carlo Methods in Statistical Physics PDF Author: Kurt Binder
Publisher: Springer Science & Business Media
ISBN: 3642828035
Category : Science
Languages : en
Pages : 425

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Book Description
In the seven years since this volume first appeared. there has been an enormous expansion of the range of problems to which Monte Carlo computer simulation methods have been applied. This fact has already led to the addition of a companion volume ("Applications of the Monte Carlo Method in Statistical Physics", Topics in Current Physics. Vol . 36), edited in 1984, to this book. But the field continues to develop further; rapid progress is being made with respect to the implementation of Monte Carlo algorithms, the construction of special-purpose computers dedicated to exe cute Monte Carlo programs, and new methods to analyze the "data" generated by these programs. Brief descriptions of these and other developments, together with numerous addi tional references, are included in a new chapter , "Recent Trends in Monte Carlo Simulations" , which has been written for this second edition. Typographical correc tions have been made and fuller references given where appropriate, but otherwise the layout and contents of the other chapters are left unchanged. Thus this book, together with its companion volume mentioned above, gives a fairly complete and up to-date review of the field. It is hoped that the reduced price of this paperback edition will make it accessible to a wide range of scientists and students in the fields to which it is relevant: theoretical phYSics and physical chemistry , con densed-matter physics and materials science, computational physics and applied mathematics, etc.

Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics

Monte-Carlo Methods and Applications in Neutronics, Photonics, and Statistical Physics PDF Author: Raymond Alcouffe
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 500

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Book Description


Applications of the Monte Carlo Method in Statistical Physics

Applications of the Monte Carlo Method in Statistical Physics PDF Author: Kurt Binder
Publisher: Springer Science & Business Media
ISBN: 364251703X
Category : Science
Languages : en
Pages : 350

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Book Description
Deals with the computer simulation of complex physical sys- tems encounteredin condensed-matter physics and statistical mechanics as well as in related fields such as metallurgy, polymer research, lattice gauge theory and quantummechanics.

A Guide to Monte Carlo Simulations in Statistical Physics

A Guide to Monte Carlo Simulations in Statistical Physics PDF Author: David P. Landau
Publisher: Cambridge University Press
ISBN: 113948043X
Category : Science
Languages : en
Pages : 489

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Book Description
Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. This edition now contains material describing powerful new algorithms that have appeared since the previous edition was published, and highlights recent technical advances and key applications that these algorithms now make possible. Updates also include several new sections and a chapter on the use of Monte Carlo simulations of biological molecules. Throughout the book there are many applications, examples, recipes, case studies, and exercises to help the reader understand the material. It is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.

A Guide to Monte Carlo Simulations in Statistical Physics

A Guide to Monte Carlo Simulations in Statistical Physics PDF Author: David Landau
Publisher: Cambridge University Press
ISBN: 1108809294
Category : Science
Languages : en
Pages : 583

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Book Description
Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. The 5th edition contains extensive new material describing numerous powerful algorithms and methods that represent recent developments in the field. New topics such as active matter and machine learning are also introduced. Throughout, there are many applications, examples, recipes, case studies, and exercises to help the reader fully comprehend the material. This book is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.

A Guide to Monte Carlo Simulations in Statistical Physics

A Guide to Monte Carlo Simulations in Statistical Physics PDF Author: David P. Landau
Publisher: Cambridge University Press
ISBN: 9780521653664
Category : Mathematics
Languages : en
Pages : 402

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Book Description
This book describes all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields, such as polymer science and lattice gauge theory. The authors give a succinct overview of simple sampling methods and develop the importance sampling method. In addition they introduce 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. The book includes many applications, examples, and current references, and exercises to help the reader.

The Monte Carlo Methods

The Monte Carlo Methods PDF Author: Abdo Abou Jaoudé
Publisher: BoD – Books on Demand
ISBN: 1839687592
Category : Science
Languages : en
Pages : 234

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Book Description
In applied mathematics, the name Monte Carlo is given to the method of solving problems by means of experiments with random numbers. This name, after the casino at Monaco, was first applied around 1944 to the method of solving deterministic problems by reformulating them in terms of a problem with random elements, which could then be solved by large-scale sampling. But, by extension, the term has come to mean any simulation that uses random numbers. Monte Carlo methods have become among the most fundamental techniques of simulation in modern science. This book is an illustration of the use of Monte Carlo methods applied to solve specific problems in mathematics, engineering, physics, statistics, and science in general.

Monte Carlo Methods in Statistical Physics

Monte Carlo Methods in Statistical Physics PDF Author: M. E. J. Newman
Publisher: Clarendon Press
ISBN: 0191589861
Category : Science
Languages : en
Pages : 490

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Book Description
This book provides an introduction to Monte Carlo simulations in classical statistical physics and is aimed both at students beginning work in the field and at more experienced researchers who wish to learn more about Monte Carlo methods. The material covered includes methods for both equilibrium and out of equilibrium systems, and common algorithms like the Metropolis and heat-bath algorithms are discussed in detail, as well as more sophisticated ones such as continuous time Monte Carlo, cluster algorithms, multigrid methods, entropic sampling and simulated tempering. Data analysis techniques are also explained starting with straightforward measurement and error-estimation techniques and progressing to topics such as the single and multiple histogram methods and finite size scaling. The last few chapters of the book are devoted to implementation issues, including discussions of such topics as lattice representations, efficient implementation of data structures, multispin coding, parallelization of Monte Carlo algorithms, and random number generation. At the end of the book the authors give a number of example programmes demonstrating the applications of these techniques to a variety of well-known models.