A Multilevel Monte Carlo Ensemble Scheme for Random Parabolic PDEs

DOI10.1137/18M1174635zbMATH Open1407.65015arXiv1802.05743OpenAlexW2912941200WikidataQ114074303 ScholiaQ114074303MaRDI QIDQ4623146

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Publication date: 19 February 2019

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Abstract: A first-order, Monte Carlo ensemble method has been recently introduced for solving parabolic equations with random coefficients in [26], which is a natural synthesis of the ensemble-based, Monte Carlo sampling algorithm and the ensemble-based, first-order time stepping scheme. With the introduction of an ensemble average of the diffusion function, this algorithm leads to a single discrete system with multiple right-hand sides for a group of realizations, which could be solved more efficiently than a sequence of linear systems. In this paper, we pursue in the same direction and develop a new multilevel Monte Carlo ensemble method for solving random parabolic partial differential equations. Comparing with the approach in [26], this method possesses a high-order accuracy in time and further reduces the computational cost by using the multilevel Monte Carlo method. Rigorous numerical analysis shows the method achieves the optimal rate of convergence. Several numerical experiments are presented to illustrate the theoretical results.

Full work available at URL: https://arxiv.org/abs/1802.05743

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