An efficient numerical approach for stochastic evolution PDEs driven by random diffusion coefficients and multiplicative noise
Author:
Affiliation:
1. School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High Performance Scientific Computing, Xiamen University, 361005 Xiamen, China
2. Bordeaux INP, Laboratoire I2M UMR 5295, 33607 Pessac, France
Abstract
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
General Mathematics
Reference70 articles.
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4. I. Babu$\check{\mathrm{s}}$ka, R. Tempone, G. E. Zouraris, Galerkin finite element approximations of stochastic elliptic partial differential equations, SIAM J. Numer. Anal., 42 (2004), 800–825. https://doi.org/10.1137/S0036142902418680
5. M. Beccari, M. Hutzenthaler, A. Jentzen, R. Kurniawan, F. Lindner, D. Salimova, Strong and weak divergence of exponential and linear-implicit euler approximations for stochastic partial differential equations with superlinearly growing nonlinearities, arXiv preprint arXiv: 1903.06066, 2019.
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1. An efficient approximation to the stochastic Allen-Cahn equation with random diffusion coefficient field and multiplicative noise;Advances in Computational Mathematics;2023-09-27
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