{
  "annotation_id": "91d83a55-8dfa-4c00-8b02-9af15fa0be4e",
  "date_created": "2026-03-02T18:02:45.075000Z",
  "date_modified": "2026-03-02T18:02:45.075000Z",
  "file_hash": "307d30758bc9366928ac9566cd8f577d2320591eaa7b4ecf1fa41d9498ac5f74",
  "private": false,
  "record": {
    "abstract": "An adaptive optimization technique to improve precision of quantum homodyne\ntomography is presented. The method is based on the existence of so-called null\nfunctions, which have zero average for arbitrary state of radiation. Addition\nof null functions to the tomographic kernels does not affect their mean values,\nbut changes statistical errors, which can then be reduced by an optimization\nmethod that \"adapts\" kernels to homodyne data. Applications to tomography of\nthe density matrix and other relevant field-observables are studied in detail.",
    "arxiv_id": "quant-ph/9812028",
    "authors": [
      "Giacomo M. D\u0027Ariano",
      "Matteo G. A. Paris"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.1103/PhysRevA.60.518",
    "journal_ref": "Phys.Rev. A60 (1999) 518",
    "title": "Adaptive Quantum Homodyne Tomography",
    "url": "https://arxiv.org/abs/quant-ph/9812028"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "8442376d-e145-40cf-9bf5-e9522f8527ac",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}