{
  "annotation_id": "f93be15a-9937-4e10-8d98-c0c9eec420fb",
  "date_created": "2026-03-02T18:01:49.269000Z",
  "date_modified": "2026-03-02T18:01:49.269000Z",
  "file_hash": "44bdd9bf728c7cd5cca3503936ae6f3a680f2e845ba4b91a35397faae7c69d6c",
  "private": false,
  "record": {
    "abstract": "We have constructed a simple semiclassical model of neural network where\nneurons have quantum links with one another in a chosen way and affect one\nanother in a fashion analogous to action potentials. We have examined the role\nof stochasticity introduced by the quantum potential and compare the system\nwith the classical system of an integrate-and-fire model by Hopfield. Average\nperiodicity and short term retentivity of input memory are noted.",
    "arxiv_id": "quant-ph/0202015",
    "authors": [
      "Fariel Shafee"
    ],
    "categories": [
      "quant-ph",
      "cond-mat.dis-nn",
      "cs.AI",
      "q-bio"
    ],
    "journal_ref": "stochastics and dynamics, Vol. 7, No. 3 (2007) 403-416",
    "title": "Semiclassical Neural Network",
    "url": "https://arxiv.org/abs/quant-ph/0202015"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "0abb215f-ab42-496a-9be8-e5b05193ae6d",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}