{
  "annotation_id": "55ecb73a-24ff-4d7d-ab66-24520f42d427",
  "date_created": "2026-03-02T18:02:34.481000Z",
  "date_modified": "2026-03-02T18:02:34.481000Z",
  "file_hash": "86fdf8cf09f97b03d3c8517053bbd9cca5822f373901315e8e0b062dd862d5de",
  "private": false,
  "record": {
    "abstract": "Quantum algorithms can be analyzed in a query model to compute Boolean\nfunctions where input is given in a black box, but the aim is to compute\nfunction value for arbitrary input using as few queries as possible. In this\npaper we concentrate on quantum query algorithm designing tasks. The main aim\nof research was to find new efficient algorithms and develop general algorithm\ndesigning techniques. We present several exact quantum query algorithms for\ncertain problems that are better than classical counterparts. Next we introduce\nalgorithm transformation methods that allow significant enlarging of sets of\nexactly computable functions. Finally, we propose algorithm constructing\nmethods applicable for algorithms with specific properties that allow\nconstructing algorithms for more complex functions preserving acceptable error\nprobability and number of queries.",
    "arxiv_id": "quant-ph/0611213",
    "authors": [
      "Alina Dubrovska Vasilieva",
      "Taisia Mischenko-Slatenkova"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "Quantum Query Algorithms for Certain Problems and Generalization of   Algorithm Designing Techniques",
    "url": "https://arxiv.org/abs/quant-ph/0611213"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "70fab2d2-035b-48cb-b87b-fbca36cd9e8f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}