{
  "annotation_id": "440bae1e-7065-40eb-ac08-a614da58ede8",
  "date_created": "2026-03-02T18:00:47.003000Z",
  "date_modified": "2026-03-02T18:00:47.003000Z",
  "file_hash": "5af1015975c461d07659cb1c6ae2ad507b66955e13a166b3b5f1c98b4cef80c2",
  "private": false,
  "record": {
    "abstract": "RooFit is a library of C++ classes that facilitate data modeling in the ROOT\nenvironment. Mathematical concepts such as variables, (probability density)\nfunctions and integrals are represented as C++ objects. The package provides a\nflexible framework for building complex fit models through classes that mimic\nmath operators, and is straightforward to extend. For all constructed models\nRooFit provides a concise yet powerful interface for fitting (binned and\nunbinned likelihood, chi^2), plotting and toy Monte Carlo generation as well as\nsophisticated tools to manage large scale projects. RooFit has matured into an\nindustrial strength tool capable of running the BABAR experiment\u0027s most\ncomplicated fits and is now available to all users on SourceForge.",
    "arxiv_id": "physics/0306116",
    "authors": [
      "Wouter Verkerke",
      "David Kirkby"
    ],
    "categories": [
      "physics.data-an"
    ],
    "title": "The RooFit toolkit for data modeling",
    "url": "https://arxiv.org/abs/physics/0306116"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "b33b6ff9-4cb6-4603-8147-27cee31d73e5",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}