{
  "annotation_id": "26845849-57c3-474c-83d0-0d91c854911a",
  "date_created": "2026-03-02T18:01:49.019000Z",
  "date_modified": "2026-03-02T18:01:49.019000Z",
  "file_hash": "776df361d9a392156f84cfa74b77ade6fac380e3af3a791cf838e76e7681c80c",
  "private": false,
  "record": {
    "abstract": "Quantum computing was so far mainly concerned with discrete problems.\n  Recently, E. Novak and the author studied quantum algorithms for high\ndimensional integration and dealt with the question, which advantages quantum\ncomputing can bring over classical deterministic or randomized methods for this\ntype of problem.\n  In this paper we give a short introduction to the basic ideas of quantum\ncomputing and survey recent results on high dimensional integration. We discuss\nconnections to the Monte Carlo methology and compare the optimal error rates of\nquantum algorithms to those of classical deterministic and randomized\nalgorithms.",
    "arxiv_id": "quant-ph/0112152",
    "authors": [
      "Stefan Heinrich"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "From Monte Carlo to Quantum Computation",
    "url": "https://arxiv.org/abs/quant-ph/0112152"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "740155d0-8237-42bc-be26-cb5154bb2e5c",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}