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

机译:抛物面随机偏微分方程不变度量的全离散指数欧拉近似

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摘要

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 - ∈ in space and 1/2 - ∈ in time for the space-time white noise case and 2 - ∈ in space and 1 - ∈ in time for the trace class noise case in space dimension d = 1, with arbitrarily small ∈ > 0. Numerical results are finally reported to confirm these theoretical findings.
机译:我们在空间尺寸D≤3中离散遍叠半线性随机偏微分方程,具有附加噪声,在空间上通过光谱Galerkin方法,并通过指数欧拉方案在时间上进行。结果表明,空间半离散化和时空全离散化是ergodic。此外,根据噪声的规律性,基于易于依赖于Malliavin微积分的易于时间缺点误差分析,回收数值不变措施的收敛订单。要精确,收敛顺序为空间1 - ∈时,空时空白色噪声箱和空间噪声箱中的空间白噪声壳和1/2‰的时间为空间尺寸d = 1,任意小∈> 0.最终报告数值结果以确认这些理论发现。

著录项

  • 来源
    《Applied numerical mathematics》 |2020年第11期|135-158|共24页
  • 作者单位

    School of Mathematics and Statistics Central South University Changsha 410083 Hunan China Institute of Computational Mathematics Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China;

    School of Mathematics and Statistics Central South University Changsha 410083 Hunan China;

    School of Mathematics and Statistics Central South University Changsha 410083 Hunan China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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

    机译:随机偏微分方程;不变措施;ergodicity;弱近似;指数欧拉方案;

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