An explicit scheme for stochastic Allen-Cahn equations with space-time white noise near the sharp interface limit
Abstract
This article investigates time-discrete approximations of Allen-Cahn type SPDEs driven by space-time white noise near the sharp interface limit , where the small parameter is the diffuse interface thickness. We propose an explicit and easily implementable exponential integrator with a modified nonlinearity for the considered problem. Uniform-in-time and uniform-in- moment bounds of the scheme are established and the convergence in total variation distance of order is established, between the law of the numerical scheme and that of the SPDE over . In contrast to the exponential dependence due to standard arguments, the obtained error bound depends on and polynomially. By incorporating carefully chosen method parameters, we only require a mild and -independent restriction on the time step-size , getting rid of the severe restriction in the literature. Also, a uniform-in-time error bound of order , is obtained for a fixed , which improves the existing ones in the literature and matches the classical weak convergence rate in the globally Lipschitz setting. The error analysis is highly nontrivial due to the low regularity of the considered problem, the super-linear growth of the drift, the non-smooth observables inherent in the total variation metric and the presence of the small interface parameter . These difficulties are addressed by introducing a new strategy of nonlinearity modification and establishing refined regularity estimates for the associated Kolmogorov equation to an auxiliary process with non-smooth test functions. Numerical experiments confirm the theoretical convergence and the ability of interface-capturing for the proposed scheme.
Keywords
Cite
@article{arxiv.2601.01894,
title = {An explicit scheme for stochastic Allen-Cahn equations with space-time white noise near the sharp interface limit},
author = {Yingsong Jiang and Chenxu Pang and Xiaojie Wang},
journal= {arXiv preprint arXiv:2601.01894},
year = {2026}
}