TriCG with deflated restarting for symmetric quasi-definite linear systems

Fuente: arXiv
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Auteurs principaux: Du, Kui, Fan, Jia-Jun
Format: Preprint
Publié: 2026
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author Du, Kui
Fan, Jia-Jun
author_facet Du, Kui
Fan, Jia-Jun
contents TriCG is a short-recurrence iterative method recently introduced by Montoison and Orban [SIAM J. Sci. Comput., 43 (2021), pp. A2502--A2525] for solving symmetric quasi-definite (SQD) linear systems. TriCG takes advantage of the inherent block structure of SQD linear systems and performs substantially better than SYMMLQ. However, numerical experiments have revealed that the convergence of TriCG can be notably slow when the off-diagonal block contains a substantial number of large elliptic singular values. To address this limitation, we introduce a deflation strategy tailored for TriCG to improve its convergence behavior. Specifically, we develop a generalized Saunders--Simon--Yip process with deflated restarting to construct the deflation subspaces. Building upon this process, we propose a novel method termed TriCG with deflated restarting. The deflation subspaces can also be utilized to solve SQD linear systems with multiple right-hand sides. Numerical experiments are provided to illustrate the superior performance of the proposed methods.
format Preprint
id arxiv_https___arxiv_org_abs_2601_07455
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle TriCG with deflated restarting for symmetric quasi-definite linear systems
Du, Kui
Fan, Jia-Jun
Numerical Analysis
65F10, 15A06, 15A18
TriCG is a short-recurrence iterative method recently introduced by Montoison and Orban [SIAM J. Sci. Comput., 43 (2021), pp. A2502--A2525] for solving symmetric quasi-definite (SQD) linear systems. TriCG takes advantage of the inherent block structure of SQD linear systems and performs substantially better than SYMMLQ. However, numerical experiments have revealed that the convergence of TriCG can be notably slow when the off-diagonal block contains a substantial number of large elliptic singular values. To address this limitation, we introduce a deflation strategy tailored for TriCG to improve its convergence behavior. Specifically, we develop a generalized Saunders--Simon--Yip process with deflated restarting to construct the deflation subspaces. Building upon this process, we propose a novel method termed TriCG with deflated restarting. The deflation subspaces can also be utilized to solve SQD linear systems with multiple right-hand sides. Numerical experiments are provided to illustrate the superior performance of the proposed methods.
title TriCG with deflated restarting for symmetric quasi-definite linear systems
topic Numerical Analysis
65F10, 15A06, 15A18
url https://arxiv.org/abs/2601.07455