Spectral analysis of block preconditioners for double saddle-point linear systems with application to PDE-constrained optimization

Fuente: arXiv
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Hauptverfasser: Bergamaschi, Luca, Martinez, Angeles, Pearson, John, Potschka, Andreas
Format: Preprint
Veröffentlicht: 2024
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author Bergamaschi, Luca
Martinez, Angeles
Pearson, John
Potschka, Andreas
author_facet Bergamaschi, Luca
Martinez, Angeles
Pearson, John
Potschka, Andreas
contents In this paper, we describe and analyze the spectral properties of a symmetric positive definite inexact block preconditioner for a class of symmetric, double saddle-point linear systems. We develop a spectral analysis of the preconditioned matrix, showing that its eigenvalues can be described in terms of the roots of a cubic polynomial with real coefficients. We illustrate the efficiency of the proposed preconditioners, and verify the theoretical bounds, in solving large-scale PDE-constrained optimization problems.
format Preprint
id arxiv_https___arxiv_org_abs_2405_14605
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Spectral analysis of block preconditioners for double saddle-point linear systems with application to PDE-constrained optimization
Bergamaschi, Luca
Martinez, Angeles
Pearson, John
Potschka, Andreas
Numerical Analysis
In this paper, we describe and analyze the spectral properties of a symmetric positive definite inexact block preconditioner for a class of symmetric, double saddle-point linear systems. We develop a spectral analysis of the preconditioned matrix, showing that its eigenvalues can be described in terms of the roots of a cubic polynomial with real coefficients. We illustrate the efficiency of the proposed preconditioners, and verify the theoretical bounds, in solving large-scale PDE-constrained optimization problems.
title Spectral analysis of block preconditioners for double saddle-point linear systems with application to PDE-constrained optimization
topic Numerical Analysis
url https://arxiv.org/abs/2405.14605