{
  "annotation_id": "63a3ce44-84fe-47a3-9b5e-55cb0672f597",
  "date_created": "2026-03-02T18:02:34.033000Z",
  "date_modified": "2026-03-02T18:02:34.033000Z",
  "file_hash": "c45cd98d73e7b44c3845e1d9f6607cb8a283ff2b2aa237fbcae5c650a17fa9ec",
  "private": false,
  "record": {
    "abstract": "Only a few classes of quantum algorithms are known which provide a speed-up\nover classical algorithms. However, these and any new quantum algorithms\nprovide important motivation for the development of quantum computers. In this\narticle new quantum algorithms are given which are based on quantum state\ntomography. These include an algorithm for the calculation of several quantum\nmechanical expectation values and an algorithm for the determination of\npolynomial factors. These quantum algorithms are important in their own right.\nHowever, it is remarkable that these quantum algorithms are immune to a large\nclass of errors. We describe these algorithms and provide conditions for\nimmunity.",
    "arxiv_id": "quant-ph/0702047",
    "authors": [
      "Lian-Ao Wu",
      "Mark S. Byrd"
    ],
    "categories": [
      "quant-ph"
    ],
    "journal_ref": "Quantum Information Processing, Vol. 8, 1 (2009)",
    "title": "Self-Protected Quantum Algorithms Based on Quantum State Tomography",
    "url": "https://arxiv.org/abs/quant-ph/0702047"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "dc5f1db3-530e-46b4-b70d-63d0517d90e7",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}