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Stochastic Numerics for Mathematical Physics /

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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 stochasti...

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Bibliographic Details
Main Author: Milʹshteĭn, G. N. (Grigoriĭ Noĭkhovich)
Corporate Author: SpringerLink (Online service)
Other Authors: Tretyakov, Michael V.
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2004.
Series:Scientific computation.
Subjects:
Physics.
Computer science.
Numerical analysis.
Distribution (Probability theory)
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Mean-Square Approximation for Stochastic Differential Equations
  • Weak Approximation for Stochastic Differential Equations
  • Numerical Methods for SDEs with Small Noise
  • Stochastic Hamiltonian Systems and Langevin Type Equations
  • Simulation of Space and Space-Time Bounded Diffusions
  • Random Walks for Linear Boundary Value Problems
  • Probabilistic Approach to Numerical Solution of the Cauchy Problem for Nonlinear Parabolic Equations
  • Numerical Solution of the Nonlinear Dirichlet and Neumann Problems Based on the Probabilistic Approach
  • Application of Stochastic Numerics to Models with Stochastic Resonance and to Brownian Ratchets
  • Appendix: Practical Guidance to Implementation of the Stochastic Numerical Methods
  • References
  • Index.