Convergence of an operator splitting scheme for abstract stochastic evolution equations

Fuente: arXiv
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Main Authors: Padgett, Joshua L, Sheng, Qin
Format: Preprint
Published: 2019
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author Padgett, Joshua L
Sheng, Qin
author_facet Padgett, Joshua L
Sheng, Qin
contents In this paper we study the convergence of a Lie-Trotter operator splitting for stochastic semi-linear evolution equations in a Hilbert space. The abstract Hilbert space setting allows for the consideration of convergence of the approximation for both the original and spatially discretized problems. It is known that the strong convergence of this scheme is classically of half-order, at best. We demonstrate that this is in fact the optimal order of convergence in the proposed setting, with the actual order being dependent upon the regularity of noise collected from applications.
format Preprint
id arxiv_https___arxiv_org_abs_1901_06371
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle Convergence of an operator splitting scheme for abstract stochastic evolution equations
Padgett, Joshua L
Sheng, Qin
Numerical Analysis
In this paper we study the convergence of a Lie-Trotter operator splitting for stochastic semi-linear evolution equations in a Hilbert space. The abstract Hilbert space setting allows for the consideration of convergence of the approximation for both the original and spatially discretized problems. It is known that the strong convergence of this scheme is classically of half-order, at best. We demonstrate that this is in fact the optimal order of convergence in the proposed setting, with the actual order being dependent upon the regularity of noise collected from applications.
title Convergence of an operator splitting scheme for abstract stochastic evolution equations
topic Numerical Analysis
url https://arxiv.org/abs/1901.06371