{
  "annotation_id": "4622d2a1-e90a-4faf-8713-f317d01a26fd",
  "date_created": "2026-03-02T18:01:38.918000Z",
  "date_modified": "2026-03-02T18:01:38.918000Z",
  "file_hash": "ac814efcd1f1536c39700b39cde7388dd03a4dbd29f7c4224d1fdcca3005d9c9",
  "private": false,
  "record": {
    "abstract": "Given two unsorted lists each of length N that have a single common entry, a\nquantum computer can find that matching element with a work factor of\n$O(N^{3/4}\\log N)$ (measured in quantum memory accesses and accesses to each\nlist). The amount of quantum memory required is $O(N^{1/2})$. The quantum\nalgorithm that accomplishes this consists of an inner Grover search combined\nwith a partial sort all sitting inside of an outer Grover search.",
    "arxiv_id": "quant-ph/0006136",
    "authors": [
      "Mark Heiligman"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "Finding Matches between Two Databases on a Quantum Computer",
    "url": "https://arxiv.org/abs/quant-ph/0006136"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "df4739d0-7bcd-4bc4-b0e5-c15aada0fe10",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}