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Bibliographic Details
Main Authors: Akrivis, Georgios, Lin, Qingle, Zhou, Zhi
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2605.28059
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author Akrivis, Georgios
Lin, Qingle
Zhou, Zhi
author_facet Akrivis, Georgios
Lin, Qingle
Zhou, Zhi
contents The parareal algorithm is a powerful parallel-in-time integration method that accelerates the numerical solution of evolution equations by iteratively combining a fine propagator and a coarse propagator. Although the convergence of the parareal algorithm has been extensively studied, most existing analyses assume that the fine propagator is either an exact solver or a single-step method. In this paper, we construct and analyze a parareal algorithm for solving parabolic equations, where the fine propagator is based on the two-step backward differentiation formula (BDF2), while the coarse propagator remains a single-step method. We propose a novel approach to design an effective correction for the initialization steps and establish linear convergence of the iteration. Numerical results fully support the theoretical findings, show clear improvements over existing multistep parareal strategies, and indicate that the proposed approach extends effectively to higher-order BDF methods and to nonlinear problems.
format Preprint
id arxiv_https___arxiv_org_abs_2605_28059
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Convergence analysis of a parareal algorithm with multistep fine propagator
Akrivis, Georgios
Lin, Qingle
Zhou, Zhi
Numerical Analysis
65M55
The parareal algorithm is a powerful parallel-in-time integration method that accelerates the numerical solution of evolution equations by iteratively combining a fine propagator and a coarse propagator. Although the convergence of the parareal algorithm has been extensively studied, most existing analyses assume that the fine propagator is either an exact solver or a single-step method. In this paper, we construct and analyze a parareal algorithm for solving parabolic equations, where the fine propagator is based on the two-step backward differentiation formula (BDF2), while the coarse propagator remains a single-step method. We propose a novel approach to design an effective correction for the initialization steps and establish linear convergence of the iteration. Numerical results fully support the theoretical findings, show clear improvements over existing multistep parareal strategies, and indicate that the proposed approach extends effectively to higher-order BDF methods and to nonlinear problems.
title Convergence analysis of a parareal algorithm with multistep fine propagator
topic Numerical Analysis
65M55
url https://arxiv.org/abs/2605.28059