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Stochastic Numerics for Mathematical Physics

  • Book
  • © 2004

Overview

  • This book contains much material never published before in book form
  • Includes supplementary material: sn.pub/extras

Part of the book series: Scientific Computation (SCIENTCOMP)

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Table of contents (9 chapters)

Keywords

About this book

Stochastic differential equations have many applications in the natural sciences. Besides, the employment of probabilistic representations together with the Monte Carlo technique allows us to reduce solution of multi-dimensional problems for partial differential equations to integration of stochastic equations. This approach leads to powerful computational mathematics that is presented in the treatise. The authors propose many new special schemes, some published here for the first time. In the second part of the book they construct numerical methods for solving complicated problems for partial differential equations occurring in practical applications, both linear and nonlinear. All the methods are presented with proofs and hence founded on rigorous reasoning, thus giving the book textbook potential. An overwhelming majority of the methods are accompanied by the corresponding numerical algorithms which are ready for implementation in practice. The book addresses researchers and graduate students in numerical analysis, physics, chemistry, and engineering as well as mathematical biology and financial mathematics.

Reviews

From the reviews of the first edition:

"Milstein and Tretyakov's book is a significant contribution to stochastic numerics. It is essential reading for anyone with serious interest in the field, either theoretical or practical." (Mathematical Reviews, 2005)

"The monograph presents research results of the authors concerning the numerical treatment of stochastic differential equations. … The book is written in the style of a research exposition. It provides a rich source of mathematical theory, examples and insightful remarks and is thus essential material for those who are interested in the subject, from both a theoretical and practical viewpoint." (Evelyn Buckwar, Zentralblatt MATH, Vol. 1085, 2006)

Authors and Affiliations

  • Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany

    Grigori N. Milstein

  • Department of Mathematics, Ural State University, Ekaterinburg, Russia

    Grigori N. Milstein

  • Department of Mathematics, University of Leicester, Leicester, UK

    Michael V. Tretyakov

Bibliographic Information

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