{
  "annotation_id": "5c7d0310-3aa9-4c04-9eb1-f150d8922a7b",
  "date_created": "2026-03-02T18:02:19.358000Z",
  "date_modified": "2026-03-02T18:02:19.358000Z",
  "file_hash": "8c0e5b1f36b45ea9d1d2a591748fb4b68b6716c13cf9c472dac93dfcdbd90a2b",
  "private": false,
  "record": {
    "abstract": "The quantum basin hopping algorithm for continuous global optimisation\ncombines a local search with Grover\u0027s algorithm, and can locate the global\noptimum using effort proportional to the square root of the number of basins.\nThis article establishes that Jordan\u0027s quantum gradient estimation method can\nbe incorporated into the quantum basin hopper, providing an extra acceleration\nproportional to the domain dimension.",
    "arxiv_id": "quant-ph/0507193",
    "authors": [
      "David Bulger"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "Quantum basin hopping with gradient-based local optimisation",
    "url": "https://arxiv.org/abs/quant-ph/0507193"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "4684a664-ab77-4528-b12f-13d5f63b24cf",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}