Wong–Zakai approximation of a stochastic partial differential equation with multiplicative noise

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Wong–Zakai approximation of a stochastic partial differential equation with multiplicative noise. / Hausenblas, Erika; Randrianasolo, Tsiry.
In: Applicable Analysis, Vol. 2024, No. 103, 19.03.2024.

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@article{7548d1b44ed94b5992671b05b3fadf8f,
title = "Wong–Zakai approximation of a stochastic partial differential equation with multiplicative noise",
abstract = "AbstractIn this article, we derive the convergence rate for the Wong–Zakai equation of some approximation of stochastic evolution equations with multiplicative noise. To be more precise, the diffusion coefficient in front of the noise is the multiplication operator, and, is therefore not bounded, a situation not treated in the literature. Since our motivation comes from problems in numerical ling, we consider a finite, high-dimensional problem approximating a stochastic evolution equation on a random time grid. By imposing suitable stability conditions on the drift term and the time grid, we achieve a convergence rate in the mean square of order min⁡{1−𝛿,2−2⁢𝛾}, for some 0<𝛿<1 and 0<𝛾<1/2.",
keywords = "multiplicative noise, partial differential equations with randomness, Stochastic partial differential equations, time-discretization scheme, Wong–Zakai approximation",
author = "Erika Hausenblas and Tsiry Randrianasolo",
note = "Publisher Copyright: {\textcopyright} 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.",
year = "2024",
month = mar,
day = "19",
doi = "10.1080/00036811.2024.2331026",
language = "English",
volume = "2024",
journal = "Applicable Analysis",
issn = "0003-6811",
number = "103",

}

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TY - JOUR

T1 - Wong–Zakai approximation of a stochastic partial differential equation with multiplicative noise

AU - Hausenblas, Erika

AU - Randrianasolo, Tsiry

N1 - Publisher Copyright: © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

PY - 2024/3/19

Y1 - 2024/3/19

N2 - AbstractIn this article, we derive the convergence rate for the Wong–Zakai equation of some approximation of stochastic evolution equations with multiplicative noise. To be more precise, the diffusion coefficient in front of the noise is the multiplication operator, and, is therefore not bounded, a situation not treated in the literature. Since our motivation comes from problems in numerical ling, we consider a finite, high-dimensional problem approximating a stochastic evolution equation on a random time grid. By imposing suitable stability conditions on the drift term and the time grid, we achieve a convergence rate in the mean square of order min⁡{1−𝛿,2−2⁢𝛾}, for some 0<𝛿<1 and 0<𝛾<1/2.

AB - AbstractIn this article, we derive the convergence rate for the Wong–Zakai equation of some approximation of stochastic evolution equations with multiplicative noise. To be more precise, the diffusion coefficient in front of the noise is the multiplication operator, and, is therefore not bounded, a situation not treated in the literature. Since our motivation comes from problems in numerical ling, we consider a finite, high-dimensional problem approximating a stochastic evolution equation on a random time grid. By imposing suitable stability conditions on the drift term and the time grid, we achieve a convergence rate in the mean square of order min⁡{1−𝛿,2−2⁢𝛾}, for some 0<𝛿<1 and 0<𝛾<1/2.

KW - multiplicative noise

KW - partial differential equations with randomness

KW - Stochastic partial differential equations

KW - time-discretization scheme

KW - Wong–Zakai approximation

UR - http://www.scopus.com/inward/record.url?scp=85188542463&partnerID=8YFLogxK

UR - https://pureadmin.unileoben.ac.at/portal/en/publications/wongzakai-approximation-of-a-stochastic-partial-differential-equation-with-multiplicative-noise(7548d1b4-4ed9-4b59-9267-1b05b3fadf8f).html

U2 - 10.1080/00036811.2024.2331026

DO - 10.1080/00036811.2024.2331026

M3 - Article

VL - 2024

JO - Applicable Analysis

JF - Applicable Analysis

SN - 0003-6811

IS - 103

ER -