Identification of Heavy-Flavour Jets With the Cms Detector in Pp Collisions at 13 Tev
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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 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). © 2018 CERN for the benefit of the CMS collaboration.
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Particle Identification Methods, Pattern Recognition, Cluster Finding, Calibration And Fitting Methods, Performance Of High Energy Physics Detectors, Performance Of High Energy Physics Detectors, Genel Fizik, Temel Bilimler (SCI), Particle identification methods; Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors;, Particle identification methods, cluster finding, Particle identification methods; Pattern recognition, cluster finding,; calibration and fitting methods; Performance of High Energy Physics; Detectors; GLUON SPLITTING RATE; HADRONIC Z-DECAYS; GEANT4; PAIRS, Instruments & Instrumentation, PAIRS, track data analysis, Physics, GLUON SPLITTING RATE, H2020, PHYSICS, MATHEMATICAL, calibration and fitting method, heavy quark: particle identification, Particle identification methods; Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors; Instrumentation; Mathematical Physics, Physical Sciences, Engineering and Technology, PARTICLE PHYSICS, Physics - Instrumentation and Detector, European Research Council, General Physics, p p: scattering, [PHYS.HEXP] Physics [physics]/High Energy Physics - Experiment [hep-ex], 610, Engineering, Computing & Technology (ENG), Engineering & allied operations, GEANT4, Science & Technology, PARTICLE PHYSICS;LARGE HADRON COLLIDER;CMS, LARGE HADRON COLLIDER, Matematiksel Fizik, Consolidator Grant, 620, Enstrümantasyon, Performance of High Energy Physics, [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], QC Physics / fizika, Performance of High Energy Physics Detectors, Mühendislik ve Teknoloji, egi, info:eu-repo/classification/ddc/620, Particle identification methods, Pattern recognition, cluster findin, calibration and fitting methods, Performance of High Energy Physics Detectors., Technology, Physics - Instrumentation and Detectors, Mühendislik, ENGINEERING, jet: transverse momentum, High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex), [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex], ALETLER & GÖSTERİM, Particle identification methods; Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors, Instrumentation, physics.ins-det, Mathematical Physics, info:eu-repo/classification/ddc/610, EGI Federation, CMS, Pattern recognition, cluster finding, calibration and fitting methods, Temel Bilimler, FİZİK, MATEMATİK, Detectors, Instrumentation and Detectors (physics.ins-det), calibration and fitting methods, 001, Nuclear & Particles Physics, Natural Sciences (SCI), virtual, Natural Sciences, ddc:620, INSTRUMENTS & INSTRUMENTATION, data analysis method, cms, FOS: Physical sciences, Fizik, 530, PHYSICS, Particle identification method, High energy physics detectors, Pattern recognition, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], European Commission, ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Физика, EC, hep-ex, Pattern Recognition, Cluster Finding, Calibration And Fitting Methods, Particle İdentification Methods, Mühendislik, Bilişim ve Teknoloji (ENG), high energy physics ; experimental particle physics ; LHC ; CMS ; standard model, Physics and Astronomy, Fizik Bilimleri, efficiency, HADRONIC Z-DECAYS, heavy quark: jet
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01 natural sciences, 0103 physical sciences
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