{
  "annotation_id": "c5c34cb5-f0b8-4dfa-9cb1-7256494993f1",
  "date_created": "2026-03-02T18:00:46.226000Z",
  "date_modified": "2026-03-02T18:00:46.226000Z",
  "file_hash": "3c9e53340469a71c36794d9098a8a0b5ff795fe988400d4697e8a62955a395b9",
  "private": false,
  "record": {
    "abstract": "The ALICE High Level Trigger has to process data online, in order to select\ninteresting (sub)events, or to compress data efficiently by modeling\ntechniques. Focusing on the main data source, the Time Projection Chamber\n(TPC), we present two pattern recognition methods under investigation: a\nsequential approach (cluster finder and track follower) and an iterative\napproach (track candidate finder and cluster deconvoluter). We show, that the\nformer is suited for pp and low multiplicity PbPb collisions, whereas the\nlatter might be applicable for high multiplicity PbPb collisions of dN/dy\u003e3000.\nBased on the developed tracking schemes we show that using modeling techniques\na compression factor of around 10 might be achievable.",
    "arxiv_id": "physics/0310052",
    "authors": [
      "V. Lindenstruth",
      "C. Loizides",
      "D. Roehrich",
      "B. Skaali",
      "T. Steinbeck",
      "R. Stock",
      "H. Tilsner",
      "K. Ullaland",
      "A. Vestbo",
      "T. Vik"
    ],
    "categories": [
      "physics.ins-det"
    ],
    "doi": "10.1109/TNS.2004.829384",
    "journal_ref": "IEEE Trans.Nucl.Sci. 51 (2004) 3; IEEE Trans.Nucl.Sci. 51 (2004)\n  383-390",
    "title": "Online Pattern Recognition for the ALICE High Level Trigger (tracking   and compression techniques)",
    "url": "https://arxiv.org/abs/physics/0310052"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "f58df626-d9bb-4680-ae3c-28435a1fbb18",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}