An all-at-once preconditioner for evolutionary partial differential equations
X.-L. Lin, M. Ng

TL;DR
This paper introduces a generalized block circulant preconditioner for evolutionary PDEs that maintains efficiency and improves convergence by incorporating a small parameter, ensuring eigenvalues cluster at 1 and enabling size-independent linear convergence.
Contribution
The paper extends existing block circulant preconditioners by adding a small parameter, preserving key properties and enhancing performance for solving evolutionary PDE systems.
Findings
Eigenvalues of the preconditioned matrix cluster at 1 for small epsilon
The generalized preconditioner maintains diagonalizability and low-rank structure
GMRES convergence rate is independent of system size with the new preconditioner
Abstract
In [McDonald, Pestana and Wathen, \textit{SIAM J. Sci. Comput.}, 40 (2018), pp. A1012--A1033], a block circulant preconditioner is proposed for all-at-once linear systems arising from evolutionary partial differential equations, in which the preconditioned matrix is proven to be diagonalizable and to have identity-plus-low-rank decomposition in the case of the heat equation. In this paper, we generalize the block circulant preconditioner by introducing a small parameter into the top-right block of the block circulant preconditioner. The implementation of the generalized preconditioner requires the same computational complexity as that of the block circulant one.Theoretically, we prove that (i) the generalization preserves the diagonalizability and the identity-plus-low-rank decomposition; (ii) all eigenvalues of the new preconditioned matrix are clustered at 1 for…
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Taxonomy
TopicsMatrix Theory and Algorithms · Electromagnetic Scattering and Analysis · Advanced Numerical Methods in Computational Mathematics
