{
  "annotation_id": "ecd0b4b3-20d2-49e9-b578-48328e3f8dcc",
  "date_created": "2026-03-02T18:02:23.425000Z",
  "date_modified": "2026-03-02T18:02:23.425000Z",
  "file_hash": "7772d0f989cf8101c6b50d36f81215b639da1e87ff27a71053b0a62de7eb46d6",
  "private": false,
  "record": {
    "abstract": "The characterization of quantum dynamics is a fundamental and central task in\nquantum mechanics. This task is typically addressed by quantum process\ntomography (QPT). Here we present an alternative \"direct characterization of\nquantum dynamics\" (DCQD) algorithm. In contrast to all known QPT methods, this\nalgorithm relies on error-detection techniques and does not require any quantum\nstate tomography. We illustrate that, by construction, the DCQD algorithm can\nbe applied to the task of obtaining partial information about quantum dynamics.\nFurthermore, we argue that the DCQD algorithm is experimentally implementable\nin a variety of prominent quantum information processing systems, and show how\nit can be realized in photonic systems with present day technology.",
    "arxiv_id": "quant-ph/0601033",
    "authors": [
      "M. Mohseni",
      "D. A. Lidar"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.1103/PhysRevLett.97.170501",
    "journal_ref": "Phys. Rev. Lett. 97, 170501 (2006)",
    "title": "Direct Characterization of Quantum Dynamics",
    "url": "https://arxiv.org/abs/quant-ph/0601033"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "8630b91f-7f68-45dd-a7fd-efdb1f53c071",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}