{
  "annotation_id": "0c494d27-ee68-44f0-8f7e-ae26e8f511ca",
  "date_created": "2026-03-02T18:02:41.110000Z",
  "date_modified": "2026-03-02T18:02:41.110000Z",
  "file_hash": "289579b48ebdf8dc90154b7e5b8a28de742005ebaae21e760f3319d3c7d9a6b7",
  "private": false,
  "record": {
    "abstract": "The using of quantum parallelism is often connected with consideration of\nquantum system with huge dimension of space of states. The n-qubit register can\nbe described by complex vector with 2^n components (it belongs to n\u0027th tensor\npower of qubit spaces). For example, for algorithm of factorization of numbers\nby quantum computer n can be about a few hundreds for some realistic\napplications for cryptography. The applications described further are used some\nother properties of quantum systems and they do not demand such huge number of\nstates.\n  The term \"images recognition\" is used here for some broad class of problems.\nFor example, we have a set of some objects V_i and function of \"likelihood\":\n  F(V,W) \u003c F(V,V) = 1\n  If we have some \"noisy\" or \"distorted\" image W, we can say that recognition\nof W is V_i, if F(W,V_i) is near 1 for some V_i.",
    "arxiv_id": "quant-ph/9703010",
    "authors": [
      "Alexander Yu. Vlasov"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "Quantum Computations and Images Recognition",
    "url": "https://arxiv.org/abs/quant-ph/9703010"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3ec22e6d-775a-4988-bc87-c4f66bbb84f1",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}