• Media type: E-Article
  • Title: FunTuple: A New N-tuple Component for Offline Data Processing at the LHCb Experiment
  • Contributor: Mathad, Abhijit; Ferrillo, Martina; Barré, Sacha; Koppenburg, Patrick; Owen, Patrick; Raven, Gerhard; Rodrigues, Eduardo; Serra, Nicola
  • imprint: Springer Science and Business Media LLC, 2024
  • Published in: Computing and Software for Big Science
  • Language: English
  • DOI: 10.1007/s41781-024-00116-1
  • ISSN: 2510-2044; 2510-2036
  • Keywords: Nuclear and High Energy Physics ; Computer Science (miscellaneous) ; Software
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>The offline software framework of the LHCb experiment has undergone a significant overhaul to tackle the data processing challenges that will arise in the upcoming Run 3 and Run 4 of the Large Hadron Collider. This paper introduces , a novel component developed for offline data processing within the LHCb experiment. This component enables the computation and storage of a diverse range of observables for both reconstructed and simulated events by leveraging on the tools initially developed for the trigger system. This feature is crucial for ensuring consistency between trigger-computed and offline-analysed observables. The component and its tool suite offer users flexibility to customise stored observables, and its reliability is validated through a full-coverage set of rigorous unit tests. This paper comprehensively explores ’s design, interface, interaction with other algorithms, and its role in facilitating offline data processing for the LHCb experiment for the next decade and beyond.</jats:p>
  • Access State: Open Access