A randomized and fully discrete Galerkin finite element method for semilinear stochastic evolution equations
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- by Raphael Kruse and Yue Wu;
- Math. Comp. 88 (2019), 2793-2825
- DOI: https://doi.org/10.1090/mcom/3421
- Published electronically: March 26, 2019
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Abstract:
In this paper the numerical solution of nonautonomous semilinear stochastic evolution equations driven by an additive Wiener noise is investigated. We introduce a novel fully discrete numerical approximation that combines a standard Galerkin finite element method with a randomized Runge–Kutta scheme. Convergence of the method to the mild solution is proven with respect to the $L^p$-norm, $p \in [2,\infty )$. We obtain the same temporal order of convergence as for Milstein–Galerkin finite element methods but without imposing any differentiability condition on the nonlinearity. The results are extended to also incorporate a spectral approximation of the driving Wiener process. An application to a stochastic partial differential equation is discussed and illustrated through a numerical experiment.References
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Bibliographic Information
- Raphael Kruse
- Affiliation: Institut für Mathematik, Technische Universität Berlin, Secr. MA 5-3, Straße des 17. Juni 136, DE-10623 Berlin, Germany
- MR Author ID: 904215
- Email: kruse@math.tu-berlin.de
- Yue Wu
- Affiliation: Institut für Mathematik, Technische Universität Berlin, Secr. MA 5-3, Straße des 17. Juni 136, DE-10623 Berlin, Germany
- MR Author ID: 1161278
- Email: wu@math.tu-berlin.de
- Received by editor(s): January 28, 2018
- Received by editor(s) in revised form: December 5, 2018
- Published electronically: March 26, 2019
- Additional Notes: The authors gratefully acknowledge financial support by the German Research Foundation through the research unit FOR 2402 – Rough paths, stochastic partial differential equations and related topics – at TU Berlin.
- © Copyright 2019 American Mathematical Society
- Journal: Math. Comp. 88 (2019), 2793-2825
- MSC (2010): Primary 65C30; Secondary 60H15, 65M12, 65M60
- DOI: https://doi.org/10.1090/mcom/3421
- MathSciNet review: 3985476