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Stochastic Numerics for Mathematical Physics /

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This book is a substantially revised and expanded edition reflecting major developments in stochastic numerics since the first edition was published in 2004. The new topics, in particular, include mean-square and weak approximations in the case of nonglobally Lipschitz coefficients of Stochastic Dif...

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Bibliographic Details
Main Authors: Milstein, Grigori N. (Author), Tretyakov, Michael V. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:2nd ed. 2021.
Series:Scientific Computation,
Subjects:
Computer mathematics.
Physics.
Chemometrics.
Applied mathematics.
Engineering mathematics.
Biomathematics.
Finance-Mathematics.
Computational Science and Engineering.
Numerical and Computational Physics, Simulation.
Math. Applications in Chemistry.
Mathematical and Computational Engineering.
Mathematical and Computational Biology.
Financial Mathematics.
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: Foundations
  • Weak Approximation for Stochastic Differential Equations: Special Cases
  • Numerical Methods for SDEs with Small Noise
  • Geometric Integrators and Computing Ergodic Limits.