Study of a TPFA scheme for the stochastic Allen-Cahn problem with constraint through numerical experiments

Fuente: arXiv
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Autori principali: Sapountzoglou, Niklas, Zimmermann, Aleksandra
Natura: Preprint
Pubblicazione: 2025
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author Sapountzoglou, Niklas
Zimmermann, Aleksandra
author_facet Sapountzoglou, Niklas
Zimmermann, Aleksandra
contents This contribution provides numerical experiments for a finite volume scheme for an approximation of the stochastic Allen-Cahn equation with homogeneous Neumann boundary conditions. The approximation is done by a Yosida approximation of the subdifferential operator. The problem is set on a polygonal bounded domain in two or three dimensions. The non-linear character of the projection term induces challenges to implement the scheme. To this end, we provide a splitting method for the finite volume scheme. We show that the splitting method is accurate. The computational error estimates induce that the squared $L^2$-error w.r.t. time is of order $1$ as long as the noise term is small enough. For larger noise terms the order of convergence w.r.t. time might become worse.
format Preprint
id arxiv_https___arxiv_org_abs_2512_17712
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Study of a TPFA scheme for the stochastic Allen-Cahn problem with constraint through numerical experiments
Sapountzoglou, Niklas
Zimmermann, Aleksandra
Numerical Analysis
Analysis of PDEs
Probability
60H15, 35K55, 65M08
This contribution provides numerical experiments for a finite volume scheme for an approximation of the stochastic Allen-Cahn equation with homogeneous Neumann boundary conditions. The approximation is done by a Yosida approximation of the subdifferential operator. The problem is set on a polygonal bounded domain in two or three dimensions. The non-linear character of the projection term induces challenges to implement the scheme. To this end, we provide a splitting method for the finite volume scheme. We show that the splitting method is accurate. The computational error estimates induce that the squared $L^2$-error w.r.t. time is of order $1$ as long as the noise term is small enough. For larger noise terms the order of convergence w.r.t. time might become worse.
title Study of a TPFA scheme for the stochastic Allen-Cahn problem with constraint through numerical experiments
topic Numerical Analysis
Analysis of PDEs
Probability
60H15, 35K55, 65M08
url https://arxiv.org/abs/2512.17712