The Galerkin analysis for the random periodic solution of semilinear stochastic evolution equations

Wu, Yue and Yuan, Chenggui (2024) The Galerkin analysis for the random periodic solution of semilinear stochastic evolution equations. Journal of Theoretical Probability, 37 (1). pp. 133-159. 2. ISSN 0894-9840 (https://doi.org/10.1007/s10959-023-01236-x)

[thumbnail of Wu-Yuan-JTP-2023-The-Galerkin-analysis-for-the-random-periodic-solution-of-semilinear-stochastic-evolution]
Preview
 Text. Filename: Wu_Yuan_JTP_2023_The_Galerkin_analysis_for_the_random_periodic_solution_of_semilinear_stochastic_evolution.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (459kB)| Preview

Abstract

In this paper we study the numerical method for approximating the random periodic solution of semilinear stochastic evolution equations. The main challenge lies in proving a convergence over an infinite time horizon while simulating infinite-dimensional objects. We first show the existence and uniqueness of the random periodic solution to the equation as the limit of the pull-back flows of the equation, and observe that its mild form is well-defined in the intersection of a family of decreasing Hilbert spaces. Then we propose a Galerkin-type exponential integrator scheme and establish its convergence rate of the strong error to the mild solution, where the order of convergence directly depends on the space (among the family of Hilbert spaces) for the initial point to live. We finally conclude with a best order of convergence that is arbitrarily close to 0.5.

CORE (COnnecting REpositories)