Exploring Monte Carlo Methods - Softcover

Dunn, William L.; Shultis, J. Kenneth

Softcover

ISBN 10: 0128197390 ISBN 13: 9780128197394

Publisher: Elsevier Science, 2022

Synopsis

Exploring Monte Carlo Methods, Second Edition provides a valuable introduction to the numerical methods that have come to be known as "Monte Carlo." This unique and trusted resource for course use, as well as researcher reference, offers accessible coverage, clear explanations and helpful examples throughout. Building from the basics, the text also includes applications in a variety of fields, such as physics, nuclear engineering, finance and investment, medical modeling and prediction, archaeology, geology and transportation planning.

• Provides a comprehensive yet concise treatment of Monte Carlo methods
• Uses the famous "Buffon’s needle problem" as a unifying theme to illustrate the many aspects of Monte Carlo methods
• Includes numerous exercises and useful appendices on: Certain mathematical functions, Bose Einstein functions, Fermi Dirac functions and Watson functions

About this title

About the Authors

Dr. Bill Dunn graduated with a BS degree in Electrical Engineering from the University of Notre Dame and MS and PhD degrees in Nuclear Engineering from North Carolina State University (NCSU). He was employed by Carolina Power & Light Company for four years and then served on the faculty and staff of the Nuclear Engineering Department at NCSU for two years. From 1979 until 2002, Dr. Dunn was involved in contract research. From 1988 until 2002, he was President of Quantum Research Services. He is now Professor and former Department Head of the Mechanical and Nuclear Engineering Department at Kansas State University. He is an editor of the journal Radiation Physics and Chemistry and Treasurer of the International Radiation Physics Society. In 2015, Dr. Dunn was recognized with the Radiation Science and Technology Award by the American Nuclear Society.

J. Kenneth Shultis, born in Toronto, Canada, graduated from the University of Toronto with a BASc degree in Engineering Physics (1964). He gained his MS (1965) and PhD (1968) degrees in Nuclear Science and Engineering from the University of Michigan. After a postdoctoral year at the Mathematics Institute of the University of Groningen, the Netherlands, he joined the Nuclear Engineering faculty at Kansas State University in 1969. He teaches and conducts research in radiation transport, radiation shielding, Monte Carlo methods, reactor physics, optimization of new type of radiation detectors, numerical analysis, particle combustion, remote sensing, and utility energy and economic analyses. He is a Fellow of the American Nuclear Society, and has received many awards for his teaching and research. Dr. Shultis is the author or co-author of 6 text books on radiation shielding, radiological assessment, nuclear science and technology, and Monte Carlo methods. He has written over 200 research papers and reports, and served as a consultant to many private and governmental organizations.

From the Back Cover

Fully and thoughtfully updated, Exploring Monte Carlo Methods, Second Edition, provides a valuable introduction to the numerical methods that have come to be known as "Monte Carlo." This unique and trusted resource for course use, as well as researcher reference, offers accessible coverage, clear explanations, and helpful examples throughout. Building from the basics, the text also includes applications in a variety of fields, such as physics, nuclear engineering, finance and investment, medical modelling and prediction, archaeology, geology, and transportation planning.

New to this Edition:

• Throughout: Expanded homework problems and additional illustrative examples
• Chapter 2: Clarification on Monte Carlo application in cases where the variance is not bounded, and distinguishing the applicability of the Law of large numbers and the Central Limit Theorem
• Chapter 3: Additional coverage on pseudorandom number generation, including discussion of the Mersenne twister generator
• Chapter 4: Expanded discussion of accuracy and precision, including more advanced estimation methods, variance of the variance, and statistical tests that can be applied to provide confidence in a Monte Carlo result
• Chapter 6: Increased coverage and additional examples on Markov Chain Monte Carlo, to give some further illustration of application to higher dimensionality problems in various fields, as well as hamiltonian (or hybrid) Monte Carlo for sampling from "difficult" distributions
• Chapter 7: Extended treatment of Symbolic Monte Carlo
• Entirely new coverage on Applications of Monte Carlo to fields such as finance and investment, medical modeling and prediction, hypothesis testing, archaeology, geology, physics, and transportation planning

Edition details

• Publisher: Elsevier Science
• Publication date: 2022
• Language: English
• ISBN 10: 0128197390
• ISBN 13: 9780128197394
• Binding: Paperback
• Edition number: 2
• Number of pages: 592