{
  "annotation_id": "1e64cbfb-9474-45e2-9d17-c0a26b29e938",
  "date_created": "2026-02-17T05:53:11.555000Z",
  "date_modified": "2026-02-17T05:53:11.555000Z",
  "file_hash": "7aff2d3e5c234f268ccd9dc82567928674f94e3426048be2b9b78422cdf7bd61",
  "private": false,
  "record": {
    "abstract": "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.",
    "arxiv_id": "2601.07455",
    "authors": [
      "Kui Du",
      "Jia-Jun Fan"
    ],
    "categories": [
      "math.NA",
      "cs.NA"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "title": "TriCG with deflated restarting for symmetric quasi-definite linear systems",
    "url": "https://arxiv.org/abs/2601.07455",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "61c67682-be8d-4ae3-b3a3-f979008b6618",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}