PreprintCC BY 4.0HAL
Domain preserving splitting schemes for a class of SPDEs driven by a standard Brownian motion
Abstract
We consider a class of SPDEs driven by a standard real-valued Brownian motion, with drift and diffusion coefficients such that there exists a unique mild solution taking values in the interval [−1,1] almost surely. To preserve this qualitative property of the exact solution, we propose a domain preserving Lie--Trotter splitting scheme: for any choice of the time-step size, the numerical solution takes values in the interval [−1,1] almost surely. Furthermore, we prove mean-square convergence with rate 1/2− for the domain preserving Lie--Trotter scheme. These theoretical results are illustrated with numerical experiments.
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BibTeX
@misc{brehier2026domain,
title = {{Domain preserving splitting schemes for a class of SPDEs driven by a standard Brownian motion}},
author = {Charles-Édouard Bréhier and David Cohen and Gijs Custers},
howpublished = {HAL},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.29950},
eprint = {2609.29950},
archivePrefix = {arXiv},
url = {https://hal.science/hal-05764532v1},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Domain preserving splitting schemes for a class of SPDEs driven by a standard Brownian motion
AU - Charles-Édouard Bréhier
AU - David Cohen
AU - Gijs Custers
PY - 2026
DA - 2026/09/24
PB - HAL
DO - 10.48550/arxiv.2609.29950
UR - https://hal.science/hal-05764532v1
AB - We consider a class of SPDEs driven by a standard real-valued Brownian motion, with drift and diffusion coefficients such that there exists a unique mild solution taking values in the interval [−1,1] almost surely. To preserve this qualitative property of the exact solution, we propose a domain preserving Lie--Trotter splitting scheme: for any choice of the time-step size, the numerical solution takes values in the interval [−1,1] almost surely. Furthermore, we prove mean-square convergence with rate 1/2− for the domain preserving Lie--Trotter scheme. These theoretical results are illustrated with numerical experiments.
ER -