Some approximation results for mild solutions of stochastic fractional order evolution equations driven by Gaussian noise

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Some approximation results for mild solutions of stochastic fractional order evolution equations driven by Gaussian noise. / Fahim, Kistosil; Hausenblas, Erika; Kovács, Mihaly.
in: Stochastics and Partial Differential Equations: Analysis and Computations, Jahrgang 11.2023, Nr. September, 26.04.2022, S. 1044-1088.

Publikationen: Beitrag in FachzeitschriftArtikelForschung(peer-reviewed)

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@article{a08f3effd91a459582e247a7357aceb3,
title = "Some approximation results for mild solutions of stochastic fractional order evolution equations driven by Gaussian noise",
abstract = "We investigate the quality of space approximation of a class of stochastic integral equations of convolution type with Gaussian noise. Such equations arise, for example, when considering mild solutions of stochastic fractional order partial differential equations but also when considering mild solutions of classical stochastic partial differential equations. The key requirement for the equations is a smoothing property of the deterministic evolution operator which is typical in parabolic type problems. We show that if one has access to nonsmooth data estimates for the deterministic error operator together with its derivative of a space discretization procedure, then one obtains error estimates in pathwise H{\"o}lder norms with rates that can be read off the deterministic error rates. We illustrate the main result by considering a class of stochastic fractional order partial differential equations and space approximations performed by spectral Galerkin methods and finite elements. We also improve an existing result on the stochastic heat equation.",
author = "Kistosil Fahim and Erika Hausenblas and Mihaly Kov{\'a}cs",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
month = apr,
day = "26",
doi = "10.1007/s40072-022-00250-0",
language = "English",
volume = "11.2023",
pages = "1044--1088",
journal = "Stochastics and Partial Differential Equations: Analysis and Computations",
issn = "2194-041x",
publisher = "Springer",
number = "September",

}

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TY - JOUR

T1 - Some approximation results for mild solutions of stochastic fractional order evolution equations driven by Gaussian noise

AU - Fahim, Kistosil

AU - Hausenblas, Erika

AU - Kovács, Mihaly

N1 - Publisher Copyright: © 2022, The Author(s).

PY - 2022/4/26

Y1 - 2022/4/26

N2 - We investigate the quality of space approximation of a class of stochastic integral equations of convolution type with Gaussian noise. Such equations arise, for example, when considering mild solutions of stochastic fractional order partial differential equations but also when considering mild solutions of classical stochastic partial differential equations. The key requirement for the equations is a smoothing property of the deterministic evolution operator which is typical in parabolic type problems. We show that if one has access to nonsmooth data estimates for the deterministic error operator together with its derivative of a space discretization procedure, then one obtains error estimates in pathwise Hölder norms with rates that can be read off the deterministic error rates. We illustrate the main result by considering a class of stochastic fractional order partial differential equations and space approximations performed by spectral Galerkin methods and finite elements. We also improve an existing result on the stochastic heat equation.

AB - We investigate the quality of space approximation of a class of stochastic integral equations of convolution type with Gaussian noise. Such equations arise, for example, when considering mild solutions of stochastic fractional order partial differential equations but also when considering mild solutions of classical stochastic partial differential equations. The key requirement for the equations is a smoothing property of the deterministic evolution operator which is typical in parabolic type problems. We show that if one has access to nonsmooth data estimates for the deterministic error operator together with its derivative of a space discretization procedure, then one obtains error estimates in pathwise Hölder norms with rates that can be read off the deterministic error rates. We illustrate the main result by considering a class of stochastic fractional order partial differential equations and space approximations performed by spectral Galerkin methods and finite elements. We also improve an existing result on the stochastic heat equation.

U2 - 10.1007/s40072-022-00250-0

DO - 10.1007/s40072-022-00250-0

M3 - Article

VL - 11.2023

SP - 1044

EP - 1088

JO - Stochastics and Partial Differential Equations: Analysis and Computations

JF - Stochastics and Partial Differential Equations: Analysis and Computations

SN - 2194-041x

SN - 2194-041X

IS - September

ER -