{
  "annotation_id": "47bffef8-3ac4-4fab-bc6d-483c3a6b6c32",
  "date_created": "2026-03-02T18:01:42.256000Z",
  "date_modified": "2026-03-02T18:01:42.256000Z",
  "file_hash": "7cde2e9e6474f40c3729d416887392998ca459729339d5be9d90454d0f589748",
  "private": false,
  "record": {
    "abstract": "Quantum adiabatic evolution provides a general technique for the solution of\ncombinatorial search problems on quantum computers. We present the results of a\nnumerical study of a particular application of quantum adiabatic evolution, the\nproblem of finding the largest clique in a random graph. An n-vertex random\ngraph has each edge included with probability 1/2, and a clique is a completely\nconnected subgraph. There is no known classical algorithm that finds the\nlargest clique in a random graph with high probability and runs in a time\npolynomial in n. For the small graphs we are able to investigate (n \u003c= 18), the\nquantum algorithm appears to require only a quadratic run time.",
    "arxiv_id": "quant-ph/0012104",
    "authors": [
      "Andrew M. Childs",
      "Edward Farhi",
      "Jeffrey Goldstone",
      "Sam Gutmann"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.26421/QIC2.3",
    "journal_ref": "Quantum Information and Computation 2, 181 (2002)",
    "title": "Finding cliques by quantum adiabatic evolution",
    "url": "https://arxiv.org/abs/quant-ph/0012104"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "27165ce3-49cb-48f4-9bda-392c60964682",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}