Robust Convergence of Parareal Algorithms with Arbitrarily High-Order Fine Propagators

Robust Convergence of Parareal Algorithms with Arbitrarily High-Order Fine Propagators

Year:    2023

Author:    Jiang Yang, Zhaoming Yuan, Zhi Zhou

CSIAM Transactions on Applied Mathematics, Vol. 4 (2023), Iss. 3 : pp. 566–591

Abstract

The aim of this paper is to analyze the robust convergence of a class of parareal algorithms for solving parabolic problems. The coarse propagator is fixed to the backward Euler method and the fine propagator is a high-order single step integrator. Under some conditions on the fine propagator, we show that there exists some critical $J_∗$ such that the parareal solver converges linearly with a convergence rate near 0.3, provided that the ratio between the coarse time step and fine time step named $J$ satisfies $J ≥ J_∗.$ The convergence is robust even if the problem data is nonsmooth and incompatible with boundary conditions. The qualified methods include all absolutely stable single step methods, whose stability function satisfies $|r(−∞)|<1,$ and hence the fine propagator could be arbitrarily high-order. Moreover, we examine some popular high-order single step methods, e.g., two-, three- and four-stage Lobatto IIIC methods, and verify that the corresponding parareal algorithms converge linearly with a factor 0.31 and the threshold for these cases is $J_∗ = 2.$ Intensive numerical examples are presented to support and complete our theoretical predictions.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/csiam-am.SO-2022-0025

CSIAM Transactions on Applied Mathematics, Vol. 4 (2023), Iss. 3 : pp. 566–591

Published online:    2023-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    26

Keywords:    Parareal algorithm parabolic problems arbitrarily high-order single step integrator convergence factor.

Author Details

Jiang Yang

Zhaoming Yuan

Zhi Zhou