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Title

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2

CollaborationWith : Ancu, Lucian Stefan / Benoit, Mathieu / Calace, Noemi / Clark, Allan Geoffrey / Coccaro, Andrea / Delitzsch, Chris Malena / Della Volpe, Domenico / Di Bello, Francesco / Dubreuil, Arnaud / Ferrere, Didier / Golling, Tobias / Gonzalez Sevilla, Sergio / Iacobucci, Giuseppe / Jansky, Roland / Katre, Akshay / Khoo, Teng Jian / Lanfermann, Marie Christine / Lionti, Anthony Eric / March Ruiz, Luis / Mermod, Philippe / Nackenhorst, Olaf / Paolozzi, Lorenzo / Schramm, Steven / Sfyrla, Anna / Valente, Marco / Wu, Xin
Published in European Physical Journal. C. 2017, vol. 77, no. 10, p. 673
Collection Open Access - SCOAP3
Abstract With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb -1 of data collected by the ATLAS experiment and simulation of proton–proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV . The impact of charged-particle separations and multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 GeV is quantified using a novel, data-driven, method. The method uses the energy loss, dE/dx , to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is 0.061±0.006(stat.)±0.014(syst.) and 0.093±0.017(stat.)±0.021(syst.) for jet transverse momenta of 200–400 GeV and 1400–1600 GeV , respectively.
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ATLAS COLLABORATION. Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2. In: European Physical Journal. C, 2017, vol. 77, n° 10, p. 673. https://archive-ouverte.unige.ch/unige:98348

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Deposited on : 2017-11-01

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