{
  "annotation_id": "4909e7e5-a6de-40e5-a0df-bb0ca53f77b4",
  "date_created": "2026-03-02T18:02:41.422000Z",
  "date_modified": "2026-03-02T18:02:41.422000Z",
  "file_hash": "b195441d8f34f91bd4843046b0ab1280e046197b4a00c4b7a54d3a7e31acf233",
  "private": false,
  "record": {
    "abstract": "Analogue computers use continuous properties of physical system for modeling.\nIn the paper is described possibility of modeling by analogue quantum computers\nfor some model of data analysis. It is analogue associative memory and a formal\nneural network. A particularity of the models is combination of continuous\ninternal processes with discrete set of output states. The modeling of the\nsystem by classical analogue computers was offered long times ago, but now it\nis not very effectively in comparison with modern digital computers. The\napplication of quantum analogue modelling looks quite possible for modern level\nof technology and it may be more effective than digital one, because number of\nelement may be about Avogadro number (N=6.0E23).",
    "arxiv_id": "quant-ph/9802028",
    "authors": [
      "Alexander Yu. Vlasov"
    ],
    "categories": [
      "quant-ph",
      "cs.CV"
    ],
    "title": "Analogue Quantum Computers for Data Analysis",
    "url": "https://arxiv.org/abs/quant-ph/9802028"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "905ff857-9021-42e0-a014-6bfc6aec1bbe",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}