Abstract
This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 hbox {fb}^{-1} of pp collision data at sqrt{s}=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of Zrightarrow mu mu and J/psi rightarrow mu mu decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of |eta |<2.7.
Highlights
The results presented in this article are obtained from an analysis of pp collision events collected by the ATLAS detector in the years from 2015 to 2018, with proton√bunches colliding every 25 ns at a centre-of-mass energy of s = 13 TeV
The results presented in this article rely primarily on a comparison of selected Z → μμ and prompt J/ψ → μμ decays in data, referred to as signal, with the corresponding Monte Carlo (MC) simulated events
Theoretical uncertainties such as the uncertainty in the knowledge of the true parton distribution functions are evaluated as the variation in the double ratio observed after reweighting the CT10 PDF set used in the Z → μμ MC simulation to MSTW2008 next-to-leading order (NLO) [50], and after considering the uncertainties associated to the MSTW2008 NLO PDF set
Summary
3 provides details of the analysed data set and simulated samples, Sect. J. C (2021) 81:578 summarises the muon candidate reconstruction process, and Sect. 5 describes the algorithms developed for optimal muon identification.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
