{
  "annotation_id": "8bfefc0e-6aed-4f64-8e7f-582182411d3c",
  "date_created": "2026-03-02T18:00:35.178000Z",
  "date_modified": "2026-03-02T18:00:35.178000Z",
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  "record": {
    "abstract": "We propose a new iterative algorithm for generating a subset of eigenvalues\nand eigenvectors of large matrices which generalizes the method of optimal\nrelaxations. We also give convergence criteria for the iterative process,\ninvestigate its efficiency by evaluating computer storage and time requirements\nand by a few numerical tests.",
    "arxiv_id": "physics/0102066",
    "authors": [
      "F. Andreozzi",
      "A. Porrino",
      "N. Lo Iudice"
    ],
    "categories": [
      "physics.gen-ph",
      "physics.comp-ph"
    ],
    "doi": "10.1088/0305-4470/35/5/101",
    "journal_ref": "J. Phys. A: Math. Gen. 35 (2002) L61-L66",
    "title": "A simple iterative algorithm for generating selected eigenspaces of   large matrices",
    "url": "https://arxiv.org/abs/physics/0102066"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e7c1150b-6185-4ef8-8e3d-2b7d86b8f914",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}