Exploring Monte Carlo Methods
- William Dunn, Kansas State University, Department of Mechanical & Nuclear Engineering, Manhattan, U.S.A.
- J. Kenneth Shultis, Kansas State University, Department of Mechanical & Nuclear Engineering, Manhattan, U.S.A.
This book provides the basic detail necessary to learn how to apply Monte Carlo methods and thus should be useful as a text book for undergraduate or graduate courses in numerical methods. It is written so that interested readers with only an understanding of calculus and differential equations can learn Monte Carlo on their own. Coverage of topics such as variance reduction, pseudo-random number generation, Markov chain Monte Carlo, inverse Monte Carlo, and linear operator equations will make the book useful even to experienced Monte Carlo practitioners.
For undergraduate or graduate courses in numerical methods and users of large, general-purpose Monte Carlo codes
- Published: April 2011
- Imprint: ELSEVIER
- ISBN: 978-0-444-51575-9
Table of Contents
2 The Basis of Monte Carlo
3 Pseudorandom Number Generators
4 Sampling, Scoring, and Precision
5 Variance Reduction Techniques
6 Markov Chain Monte Carlo
7 Inverse Monte Carlo
8 Linear Operator Equations
9 The Fundamentals of Neutral Particle Transport
10 Monte Carlo Simulation of Neutral Particle Transport