
Monte Carlo Methods For Applied Scientists
Ivan Tomov Dimov(Author)
World Scientific Publishing Co Pte Ltd
Published on 27. December 2007
Book
Hardback
308 pages
978-981-02-2329-8 (ISBN)
Description
The Monte Carlo method is inherently parallel and the extensive and rapid development in parallel computers, computational clusters and grids has resulted in renewed and increasing interest in this method. At the same time there has been an expansion in the application areas and the method is now widely used in many important areas of science including nuclear and semiconductor physics, statistical mechanics and heat and mass transfer.This book attempts to bridge the gap between theory and practice concentrating on modern algorithmic implementation on parallel architecture machines. Although a suitable text for final year postgraduate mathematicians and computational scientists it is principally aimed at the applied scientists: only a small amount of mathematical knowledge is assumed and theorem proving is kept to a minimum, with the main focus being on parallel algorithms development often to applied industrial problems.A selection of algorithms developed both for serial and parallel machines are provided.
More details
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Applied scientists and mathematicians.
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 220 mm
Width: 162 mm
Thickness: 20 mm
Weight
581 gr
ISBN-13
978-981-02-2329-8 (9789810223298)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Content
Basic Results of Monte Carlo Integration
Optimal Monte Carlo Method for Multidimensional Integrals of Smooth Functions
Iterative Monte Carlo Methods for Linear Equations
Markov Chain Monte Carlo Methods for Eigenvalue Problems
Monte Carlo Methods for Boundary-Value Problems (BVP)
Superconvergent Monte Carlo for Density Function Simulation by B-Splines
Solving Non-Linear Equations
Algorithmic Effciency for Different Computer Models
Applications for Transport Modeling in Semiconductors and Nanowires
Optimal Monte Carlo Method for Multidimensional Integrals of Smooth Functions
Iterative Monte Carlo Methods for Linear Equations
Markov Chain Monte Carlo Methods for Eigenvalue Problems
Monte Carlo Methods for Boundary-Value Problems (BVP)
Superconvergent Monte Carlo for Density Function Simulation by B-Splines
Solving Non-Linear Equations
Algorithmic Effciency for Different Computer Models
Applications for Transport Modeling in Semiconductors and Nanowires