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Numerical Ergodicity of Stochastic Allen-Cahn Equation Driven by Multiplicative White Noise

Numerical Ergodicity of Stochastic Allen-Cahn Equation Driven by Multiplicative White Noise

Year:    2025

Author:    Zhihui Liu

Communications in Mathematical Research , Vol. 41 (2025), Iss. 1 : pp. 30–44

Abstract

We establish the unique ergodicity of a fully discrete scheme for monotone SPDEs with polynomial growth drift and bounded diffusion coefficients driven by multiplicative white noise. The main ingredient of our method depends on the satisfaction of a Lyapunov condition followed by a uniform moments’ estimate, combined with the regularity property for the full discretization. We transform the original stochastic equation into an equivalent random equation where the discrete stochastic convolutions are uniformly controlled to derive the desired uniform moments’ estimate. Applying the main result to the stochastic Allen-Cahn equation driven by multiplicative white noise indicates that this full discretization is uniquely ergodic for any interface thickness. Numerical experiments validate our theoretical results.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cmr.2024-0042

Communications in Mathematical Research , Vol. 41 (2025), Iss. 1 : pp. 30–44

Published online:    2025-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    15

Keywords:    Numerical invariant measure numerical ergodicity stochastic Allen-Cahn equation.

Author Details

Zhihui Liu

  1. Numerical Unique Ergodicity of Monotone SDEs Driven by Nondegenerate Multiplicative Noise

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    https://doi.org/10.1007/s10915-025-02902-4 [Citations: 0]