ATLAS Collaboration(Aad, G. et al), Aikot, A., Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., et al. (2024). Performance and calibration of quark/gluon-jet taggers using 140 fb-1 of pp collisions at √s=13 TeV with the ATLAS detector. Chin. Phys. C, 48(2), 023001–25pp.
Abstract: The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using root s = 13 TeV proton-proton collision data with an integrated luminosity of 140 fb(-1) collected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points.
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ATLAS Collaboration(Aad, G. et al), Alvarez Piqueras, D., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fernandez Martinez, P., et al. (2016). Performance of b-jet identification in the ATLAS experiment. J. Instrum., 11, P04008–126pp.
Abstract: The identification of jets containing b hadrons is important for the physics programme of the ATLAS experiment at the Large Hadron Collider. Several algorithms to identify jets containing b hadrons are described, ranging from those based on the reconstruction of an inclusive secondary vertex or the presence of tracks with large impact parameters to combined tagging algorithms making use of multi-variate discriminants. An independent b-tagging algorithm based on the reconstruction of muons inside jets as well as the b-tagging algorithm used in the online trigger are also presented. The b-jet tagging efficiency, the c-jet tagging efficiency and the mistag rate for light flavour jets in data have been measured with a number of complementary methods. The calibration results are presented as scale factors defined as the ratio of the efficiency (or mistag rate) in data to that in simulation. In the case of b jets, where more than one calibration method exists, the results from the various analyses have been combined taking into account the statistical correlation as well as the correlation of the sources of systematic uncertainty.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). Calibration of the light-flavour jet mistagging efficiency of the b-tagging algorithms with Z plus jets events using 139 fb<SUP>-1</SUP> of ATLAS proton-proton collision data at √s=13 TeV. Eur. Phys. J. C, 83(8), 728–30pp.
Abstract: The identification of b-jets, referred to as b-tagging, is an important part of many physics analyses in the ATLAS experiment at the Large Hadron Collider and an accurate calibration of its performance is essential for high-quality physics results. This publication describes the calibration of the light-flavour jet mistagging efficiency in a data sample of proton-proton collision events at root s = 13 TeV corresponding to an integrated luminosity of 139 fb(-1). The calibration is performed in a sample of Z bosons produced in association with jets. Due to the low mistagging efficiency for light-flavour jets, a method which uses modified versions of the b-tagging algorithms referred to as flip taggers is used in this work. A fit to the jet-flavour-sensitive secondary-vertex mass is performed to extract a scale factor from data, to correct the light-flavour jet mistagging efficiency in Monte Carlo simulations, while simultaneously correcting the b-jet efficiency. With this procedure, uncertainties coming from the modeling of jets from heavy-flavour hadrons are considerably lower than in previous calibrations of the mistagging scale factors, where they were dominant. The scale factors obtained in this calibration are consistent with unity within uncertainties.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., Castillo, F. L., et al. (2021). Measurement of b-quark fragmentation properties in jets using the decay B-+/- -> J/psi K-+/- in pp collisions at root s=13 TeV with the ATLAS detector. J. High Energy Phys., 12(12), 131–46pp.
Abstract: The fragmentation properties of jets containing b-hadrons are studied using charged B mesons in 139fb(-1) of pp collisions at root s = 13 TeV, recorded with the ATLAS detector at the LHC during the period from 2015 to 2018. The B mesons are reconstructed using the decay of B-+/- into J/psi K-+/-, with the J/psi decaying into a pair of muons. Jets are reconstructed using the anti-k(t) algorithm with radius parameter R = 0.4. The measurement determines the longitudinal and transverse momentum profiles of the reconstructed B hadrons with respect to the axes of the jets to which they are geometrically associated. These distributions are measured in intervals of the jet transverse momentum, ranging from 50 GeV to above 100 GeV. The results are corrected for detector effects and compared with several Monte Carlo predictions using different parton shower and hadronisation models. The results for the longitudinal and transverse profiles provide useful inputs to improve the description of heavy-flavour fragmentation in jets.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset. Eur. Phys. J. C, 83(7), 681–37pp.
Abstract: The flavour-tagging algorithms developed by the AvTLAS Collaboration and used to analyse its dataset of root s = 13 TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% b-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model t (t) over bar events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.
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