Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/8692
Title: Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV
Authors: Karapınar, Güler
CMS Collaboration
Keywords: Particle identification methods
Pattern recognition, cluster finding, calibration and fitting methods
Performance of High Energy Physics Detectors
Issue Date: 2018
Publisher: IOP Publishing Ltd.
Abstract: Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated t (t) over bar events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The b jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV).
URI: https://doi.org/10.1088/1748-0221/13/05/P05011
https://hdl.handle.net/11147/8692
ISSN: 1748-0221
Appears in Collections:Rectorate / Rektörlük
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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