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Stochastic Tools in Mathematics and Science

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This introduction to probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. Topics covered include conditional expectations, stochastic processes, Langevin equations, and Markov chain Monte Carlo algorithms. The applications include data assimilation, prediction from partial data, spectral analysis and turbulence. A special feature is the systematic analysis of memory effects.

Author(s): Alexandre Chorin, Ole H. Hald (auth.)
Series: Surveys and Tutorials in the Applied Mathematical Sciences 1
Edition: 2nd ed.
Publisher: Springer New York
Year: 2009

Language: English
Pages: 172
Tags: Probability Theory and Stochastic Processes;Statistical Physics;Mechanics, Fluids, Thermodynamics;Applications of Mathematics;Engineering Fluid Dynamics

Front Matter....Pages 1-9
Preliminaries....Pages 1-17
Probability....Pages 19-46
Brownian Motion....Pages 47-81
Stationary Stochastic Processes....Pages 83-107
Statistical Mechanics....Pages 109-134
Time-Dependent Statistical Mechanics....Pages 135-159
Back Matter....Pages 1-2