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

A full-discrete exponential Euler approximation of the invariant measure for parabolic stochastic partial differential equations
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抛物型随机偏微分方程不变测度的全离散指数欧拉近似

DOI:
10.1016/j.apnum.2020.05.008
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发表时间:
2018-11
影响因子:
2.8
通讯作者:
Xiaojie Wang
Xiaojie Wang
中科院分区:
数学2区
文献类型:
--
作者:
Ziheng Chen;Siqing Gan;Xiaojie Wang

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We discrete the ergodic semilinear stochastic partial differential equations in space dimension d≤ 3 with 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− ϵ in space and 1 2− ϵ in time for the space-time white noise case and 2− ϵ in space and 1− ϵ in time for the trace class noise case in space dimension d= 1, with arbitrarily small ϵ> 0. Numerical results are finally reported to confirm these theoretical findings.
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