Stochastic Numerics for the Boltzmann Equation
Shastic numerical methods play an important role in large scale computations in the applied sciences. The first goal of this book is to give a mathematical description of classical direct simulation Monte Carlo (DSMC) procedures for rarefied gases, using the theory of Markov processes as a unifying framework. The second goal is a systematic treatment of an extension of DSMC, called shastic weighted particle method. This method includes several new features, which are introduced for the purpose of variance reduction (rare event simulation). Rigorous convergence results as well as detailed numerical studies are presented.

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Stochastic Numerics for the Boltzmann Equation
Shastic numerical methods play an important role in large scale computations in the applied sciences. The first goal of this book is to give a mathematical description of classical direct simulation Monte Carlo (DSMC) procedures for rarefied gases, using the theory of Markov processes as a unifying framework. The second goal is a systematic treatment of an extension of DSMC, called shastic weighted particle method. This method includes several new features, which are introduced for the purpose of variance reduction (rare event simulation). Rigorous convergence results as well as detailed numerical studies are presented.

109.99 In Stock
Stochastic Numerics for the Boltzmann Equation

Stochastic Numerics for the Boltzmann Equation

Stochastic Numerics for the Boltzmann Equation

Stochastic Numerics for the Boltzmann Equation

Hardcover(2005)

$109.99 
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Overview

Shastic numerical methods play an important role in large scale computations in the applied sciences. The first goal of this book is to give a mathematical description of classical direct simulation Monte Carlo (DSMC) procedures for rarefied gases, using the theory of Markov processes as a unifying framework. The second goal is a systematic treatment of an extension of DSMC, called shastic weighted particle method. This method includes several new features, which are introduced for the purpose of variance reduction (rare event simulation). Rigorous convergence results as well as detailed numerical studies are presented.


Product Details

ISBN-13: 9783540252689
Publisher: Springer Berlin Heidelberg
Publication date: 07/21/2005
Series: Springer Series in Computational Mathematics , #37
Edition description: 2005
Pages: 256
Product dimensions: 6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

Kinetic theory.- Related Markov processes.- Shastic weighted particle method.- Numerical experiments.
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