{
  "annotation_id": "eb4b4436-76c6-4a8c-9940-02757249d3c5",
  "date_created": "2026-03-02T18:02:34.493000Z",
  "date_modified": "2026-03-02T18:02:34.493000Z",
  "file_hash": "bb2293f965e3ba34c237ed27ad3b2176e9c786bd112b24f863e51f03e20fd718",
  "private": false,
  "record": {
    "abstract": "Several physical architectures allow for measurement-based quantum computing\nusing sequential preparation of cluster states by means of probabilistic\nquantum gates. In such an approach, the order in which partial resources are\ncombined to form the final cluster state turns out to be crucially important.\nWe determine the influence of this classical decision process on the expected\nsize of the final cluster. Extending earlier work, we consider different\nquantum gates operating at various probabilites of success. For finite\nresources, we employ a computer algebra system to obtain the provably optimal\nclassical control strategy and derive symbolic results for the expected final\nsize of the cluster. We identify two regimes: When the success probability of\nthe elementary gates is high, the influence of the classical control strategy\nis found to be negligible. In that case, other figures of merit become more\nrelevant. In contrast, for small probabilities of success, the choice of an\nappropriate strategy is crucial.",
    "arxiv_id": "quant-ph/0703045",
    "authors": [
      "K. Kieling",
      "D. Gross",
      "J. Eisert"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.1088/1367-2630/9/6/200",
    "journal_ref": "New J. Phys. 9, 200 (2007)",
    "title": "Cluster state preparation using gates operating at arbitrary success   probabilities",
    "url": "https://arxiv.org/abs/quant-ph/0703045"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "9ea722ea-a57b-4b91-83ab-c287d7462d9b",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}