{
  "annotation_id": "aa10692d-69ed-4a70-8ff6-6e76e6d734d0",
  "date_created": "2026-03-02T18:00:43.057000Z",
  "date_modified": "2026-03-02T18:00:43.057000Z",
  "file_hash": "b6e84fb2344cfd080d94eae7dc716dcbf50bfe5af0033605b2e9cd270651e8ac",
  "private": false,
  "record": {
    "abstract": "We consider nearest neighbor spacing distributions of composite ensembles of\nlevels. These are obtained by combining independently unfolded sequences of\nlevels containing only few levels each. Two problems arise in the spectral\nanalysis of such data. One problem lies in fitting the nearest neighbor spacing\ndistribution to the histogram of level spacings obtained from the data. We show\nthat the method of Bayesian inference is superior to this procedure. The second\nproblem occurs when one unfolds such short sequences. We show that the\nunfolding procedure generically leads to an overestimate of the chaoticity\nparameter. This trend is absent in the presence of long-range level\ncorrelations. Thus, composite ensembles of levels from a system with long-range\nspectral stiffness yield reliable information about the chaotic behavior of the\nsystem.",
    "arxiv_id": "physics/0212049",
    "authors": [
      "A. Y. Abul-Magd",
      "H. L. Harney",
      "M. H. Simbel",
      "H. A. Weidenmueller"
    ],
    "categories": [
      "physics.data-an",
      "nucl-th"
    ],
    "doi": "10.1016/j.aop.2005.04.005",
    "journal_ref": "Annals Phys. 321 (2006) 560-580",
    "title": "Statistical Analysis of Composite Spectra",
    "url": "https://arxiv.org/abs/physics/0212049"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "fcbce001-26c6-4189-8afb-e21bf070e259",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}