An Introduction to Quantum Monte Carlo Methods

An Introduction to Quantum Monte Carlo Methods

by Tao Pang
An Introduction to Quantum Monte Carlo Methods

An Introduction to Quantum Monte Carlo Methods

by Tao Pang

eBook

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Overview

Monte Carlo methods have been very prominent in computer simulation of various systems in physics, chemistry, biology, and materials science. This book focuses on the diffusion and path-integral quantum Monte Carlo methods in many-body physics and provides a concise but complete introduction to the Metropolis algorithm and its applications in these two techniques. To explore the schemes in clarity, several quantum many-body systems are analyzed and studied in detail. The book includes exercises to help digest the materials covered. It can be used as a tutorial to learn the diffusion and path-integral Monte Carlo or a recipe for developing new research in reader’s own area. Two complete Java programs, one for the diffusion Monte Carlo of 4He clusters on a graphite surface and the other for the path-integral Monte Carlo of cold atoms in a potential trap, are ready for download and adoption.


Product Details

ISBN-13: 9781681741734
Publisher: Morgan & Claypool Publishers
Publication date: 12/07/2016
Series: IOP Concise Physics
Sold by: Barnes & Noble
Format: eBook
Pages: 80
File size: 2 MB

About the Author

Tao Pang is Professor of Physics at the University of Nevada, Las Vegas (UNLV). Following his higher education at Fudan University, China, he obtained his PhD in condensed matter theory from the University of Minnesota in 1989. He then spent two years as a Miller Research Fellow at the University of California, Berkeley, before joining the UNLV physics faculty in 1991. He has been Professor of Physics at UNLV since 2002. His main areas of research include condensed matter theory and computational physics.
Tao Pang is Professor of Physics at the University of Nevada, Las Vegas (UNLV). Following his higher education at Fudan University, one of the most prestigious institutions in China, he obtained his PhD in condensed matter theory from the University of Minnesota in 1989. He then spent two years as a Miller Research Fellow at the University of California, Berkeley, before joining the UNLV physics faculty in the fall of 1991. He has been Professor of Physics at UNLV since 2002. His main areas of research include condensed matter theory and computational physics.

Table of Contents

Table of Contents: Preface / Acknowledgements / Author biography / Chapter 1: Introduction / Chapter 2: The Metropolis algorithm / Chapter 3: Variational Monte Carlo / Chapter 4: Diffusion Monte Carlo / Chapter 5: Path-integral Monte Carlo
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