{
  "annotation_id": "66dc9566-511c-4748-8437-2be6e26d6010",
  "date_created": "2026-03-02T18:00:39.777000Z",
  "date_modified": "2026-03-02T18:00:39.777000Z",
  "file_hash": "a5a87b188bf0173289963549b20ecbc2f05e79ebee8bcc404ba037321b5b99bc",
  "private": false,
  "record": {
    "abstract": "We use the extension of the method of recurrence plots to cross recurrence\nplots (CRP) which enables a nonlinear analysis of bivariate data. To quantify\nCRPs, we develop further three measures of complexity mainly basing on diagonal\nstructures in CRPs. The CRP analysis of prototypical model systems with\nnonlinear interactions demonstrates that this technique enables to find these\nnonlinear interrelations from bivariate time series, whereas linear correlation\ntests do not. Applying the CRP analysis to climatological data, we find a\ncomplex relationship between rainfall and El Nino data.",
    "arxiv_id": "physics/0201061",
    "authors": [
      "N. Marwan",
      "J. Kurths"
    ],
    "categories": [
      "physics.data-an",
      "math-ph",
      "math.MP",
      "nlin.CD",
      "physics.geo-ph"
    ],
    "doi": "10.1016/S0375-9601(02)01170-2",
    "journal_ref": "Physics Letters A, 302(5-6), 2002, 299-307",
    "title": "Nonlinear analysis of bivariate data with cross recurrence plots",
    "url": "https://arxiv.org/abs/physics/0201061"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "52f77b07-410e-4bee-9c51-7fab7af78ebc",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}