Discrete stochastic maximal $ L^p $-regularity and convergence of a spatial semidiscretization for a linear stochastic heat equation
Numerical Analysis
2025-10-14 v8 Numerical Analysis
Probability
Abstract
This study investigates the boundedness of the -calculus for the discrete negative Laplace operator, subject to homogeneous Dirichlet boundary conditions. The discrete negative Laplace operator is implemented using the finite element method, and we establish that its -calculus is uniformly bounded with respect to the spatial mesh size. Using this finding, we derive a discrete stochastic maximal -regularity estimate for a spatial semidiscretization of a linear stochastic heat equation. Furthermore, we provide a nearly optimal pathwise uniform convergence estimate for this spatial semidiscretization within the framework of general spatial -norms.
Keywords
Cite
@article{arxiv.2311.04615,
title = {Discrete stochastic maximal $ L^p $-regularity and convergence of a spatial semidiscretization for a linear stochastic heat equation},
author = {Binjie Li and Qin Zhou},
journal= {arXiv preprint arXiv:2311.04615},
year = {2025}
}