{
  "annotation_id": "10c09248-53eb-46ed-bb2e-03864beca7ce",
  "date_created": "2026-03-02T18:00:50.485000Z",
  "date_modified": "2026-03-02T18:00:50.485000Z",
  "file_hash": "8d737eceb27917fb6a31af18016f6e09daee02c14e7882519af6574ab2c0031f",
  "private": false,
  "record": {
    "abstract": "The binary many-step Markov chain with the step-like memory function is\nconsidered as a model for the analysis of rank distributions of words in\nstochastic symbolic dynamical systems. We prove that the envelope curve for\nthis distribution obeys the power law with the exponent of the order of unity\nin the case of rather strong persistent correlations. The Zipf law is shown to\nbe valid for the rank distribution of words with lengths about and shorter than\nthe correlation length in the Markov sequence. A self-similarity in the rank\ndistribution with respect to the decimation procedure is observed.",
    "arxiv_id": "physics/0406099",
    "authors": [
      "K. E. Kechedzhy O. V. Usatenko",
      "V. A. Yampol\u0027skii"
    ],
    "categories": [
      "physics.hist-ph",
      "physics.data-an"
    ],
    "title": "Rank distributions of words in additive many-step Markov chains and the   Zipf law",
    "url": "https://arxiv.org/abs/physics/0406099"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "b77a7b00-79c6-4f65-a08f-37d1b00144bd",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}