{
  "annotation_id": "72ef838e-5ad1-4983-9be0-247c57f23519",
  "date_created": "2026-03-02T18:02:30.214000Z",
  "date_modified": "2026-03-02T18:02:30.214000Z",
  "file_hash": "4b819f06bd83108ab70a6bcc6c37fc8e8b317c59c92f7559b1580f8930797582",
  "private": false,
  "record": {
    "abstract": "Quantum oracles play key roles in the studies of quantum computation and\nquantum information. But implementing quantum oracles efficiently with\nuniversal quantum gates is a hard work. Motivated by genetic programming, this\npaper proposes a novel approach to evolve quantum oracles with a hybrid\nquantum-inspired evolutionary algorithm. The approach codes quantum circuits\nwith numerical values and combines the cost and correctness of quantum circuits\ninto the fitness function. To speed up the calculation of matrix multiplication\nin the evaluation of individuals, a fast algorithm of matrix multiplication\nwith Kronecker product is also presented. The experiments show the validity and\nthe effects of some parameters of the presented approach. And some\ncharacteristics of the novel approach are discussed too.",
    "arxiv_id": "quant-ph/0610105",
    "authors": [
      "Shengchao Ding",
      "Zhi Jin",
      "Qing Yang"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "Evolving Quantum Oracles with Hybrid Quantum-inspired Evolutionary   Algorithm",
    "url": "https://arxiv.org/abs/quant-ph/0610105"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "313066fc-5fa3-424e-a225-0786500f56bf",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}