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甘四清

Journal Publications

A full-discrete exponential Euler approximation of the invariant measure for parabolic stochastic partial differential equations

Journal:Applied Numerical Mathematics

Key Words:Stochastic partial differential equations; Invariant measure; Ergodicity; Weak approximation; Exponential Euler scheme

Abstract:We discrete the ergodic semilinear stochastic partial differential equations in space dimension d ≤3with additive noise, spatially by a spectral Galerkin method and temporally by an exponential Euler scheme. It is shown that both the spatial semi-discretization and the spatio-temporal full discretization are ergodic. Further, convergence orders of the numerical invariant measures, depending on the regularity of noise, are recovered based on an easy time-independent weak error analysis without relying on Malliavin calculus. To be precise, the convergence order is 1-epsilon in space and 1/2-epsilon in time for the space-time white noise case and 2 -epsilon in space and 1-epsilon in time for the trace class noise case in space dimension d =1, with arbitrarily small epsilon>0. Numerical results are finally reported to confirm these theoretical findings.

Co-author:Chen Ziheng, Gan Siqing, Wang Xiaojie

Indexed by:Journal paper

Document Type:J

Volume:157

Page Number:135–158

Translation or Not:no

Included Journals:SCI