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An Efficient Preconditioner for Evolutionary Partial Differential Equations with θ-Method in Time Discretization

  • Yuan Yuan Huang
  • , Po Yin Fung
  • , Sean Y. Hon*
  • , Xue Lei Lin
  • *Corresponding author for this work
  • Hong Kong Baptist University
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, the θ-method is used for discretizing a class of evolutionary partial differential equations. Then, we transform the resultant all-at-once linear system and introduce a novel one-sided preconditioner, which can be fast implemented in a parallel-in-time way. By introducing an auxiliary two-sided preconditioned system, we provide theoretical insights into the relationship between the residuals of the generalized minimal residual (GMRES) method when applied to both one-sided and two-sided preconditioned systems. Moreover, we show that the condition number of the two-sided preconditioned matrix is uniformly bounded by a constant that is independent of the matrix size, which in turn implies that the convergence behavior of the GMRES method for the one-sided preconditioned system is guaranteed. Numerical experiments confirm the efficiency and robustness of the proposed preconditioning approach.

Original languageEnglish
Article number47
JournalJournal of Scientific Computing
Volume103
Issue number2
DOIs
StatePublished - May 2025
Externally publishedYes

Keywords

  • All-at-once systems
  • Crank–Nicolson
  • Multilevel Toeplitz matrices
  • Parallel-in-time
  • Preconditioning
  • θ-Method

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