Modified equations for weakly convergent stochastic symplectic schemes via their generating functions

DOI10.1007/s10543-015-0583-8zbMath1355.65018OpenAlexW2170649762MaRDI QIDQ329031

Lijin Wang, Liying Sun, Jialin Hong

Publication date: 21 October 2016

Published in: BIT (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10543-015-0583-8

zbMATH Keywords

numerical teststochastic generating functionsstochastic Hamiltonian systemsstochastic backward error analysisstochastic modified equationsstochastic symplectic methods

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Generation, random and stochastic difference and differential equations (37H10) Numerical solutions to stochastic differential and integral equations (65C30) Numerical methods for Hamiltonian systems including symplectic integrators (65P10) Discretization methods and integrators (symplectic, variational, geometric, etc.) for dynamical systems (37M15)

Related Items (7)

Computing Effective Diffusivity of Chaotic and Stochastic Flows Using Structure-Preserving Schemes ⋮ High Order Conformal Symplectic and Ergodic Schemes for the Stochastic Langevin Equation via Generating Functions ⋮ Asymptotically-Preserving Large Deviations Principles by Stochastic Symplectic Methods for a Linear Stochastic Oscillator ⋮ Exponential discrete gradient schemes for a class of stochastic differential equations ⋮ Efficient Stochastic Runge-Kutta Methods for Stochastic Differential Equations with Small Noises ⋮ Weak backward error analysis for stochastic Hamiltonian systems ⋮ Optimal convergence rate of modified milstein scheme for SDEs with rough fractional diffusions

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