{
  "annotation_id": "9a320662-0156-4d04-bfad-83184c682269",
  "date_created": "2026-03-02T18:00:49.856000Z",
  "date_modified": "2026-03-02T18:00:49.856000Z",
  "file_hash": "e4495a00df8a8fed8961401a6057ab774b7db6bac9aabf104b5d1de92cc22517",
  "private": false,
  "record": {
    "abstract": "This report reviews methods of pattern recognition and event reconstruction\nused in modern high energy physics experiments. After a brief introduction into\ngeneral concepts of particle detectors and statistical evaluation, different\napproaches in global and local methods of track pattern recognition are\nreviewed with their typical strengths and shortcomings. The emphasis is then\nmoved to methods which estimate the particle properties from the signals which\npattern recognition has associated. Finally, the global reconstruction of the\nevent is briefly addressed.",
    "arxiv_id": "physics/0402039",
    "authors": [
      "Rainer Mankel"
    ],
    "categories": [
      "physics.data-an",
      "physics.ins-det"
    ],
    "doi": "10.1088/0034-4885/67/4/R03",
    "journal_ref": "Rept.Prog.Phys. 67 (2004) 553",
    "title": "Pattern Recognition and Event Reconstruction in Particle Physics   Experiments",
    "url": "https://arxiv.org/abs/physics/0402039"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "3d47f5cc-9109-4633-989b-20e263906d8f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}