Calibration of a soft secondary vertex tagger using proton-proton collisions at Formula Presented with the ATLAS detector


Filmer E., Grant C., Green M., Jackson P., Kong A., Pandya H., ...Daha Fazla

Physical Review D, cilt.110, sa.3, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 110 Sayı: 3
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1103/physrevd.110.032015
  • Dergi Adı: Physical Review D
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Chemical Abstracts Core, INSPEC, zbMATH, Nature Index
  • Ankara Üniversitesi Adresli: Evet

Özet

Several processes studied by the ATLAS experiment at the Large Hadron Collider produce low-momentum Formula Presented-flavored hadrons in the final state. This paper describes the calibration of a dedicated tagging algorithm that identifies Formula Presented-flavored hadrons outside of hadronic jets by reconstructing the soft secondary vertices originating from their decays. The calibration is based on a proton-proton collision dataset at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of Formula Presented. Scale factors used to correct the algorithm’s performance in simulated events are extracted for the Formula Presented-tagging efficiency and the mistag rate of the algorithm using a data sample enriched in Formula Presented events. Several orthogonal measurement regions are defined, binned as a function of the multiplicities of soft secondary vertices and jets containing a Formula Presented-flavored hadron in the event. The mistag rate scale factors are estimated separately for events with low and high average numbers of interactions per bunch crossing. The results, which are derived from events with low missing transverse momentum, are successfully validated in a phase space characterized by high missing transverse momentum and therefore are applicable to new physics searches carried out in either phase space regime.