Muon reconstruction and identification efficiency in ATLAS using the full Run 2 $pp$ collision data set at $\sqrt{s}=13$ TeV

TL;DR

This paper reports on the precise measurement of muon reconstruction and identification efficiencies in the ATLAS experiment using the full Run 2 dataset at 13 TeV, highlighting algorithm improvements and high accuracy results across a broad kinematic range.

Contribution

It introduces new algorithms and reoptimizes criteria for muon identification in high-luminosity conditions, achieving high efficiency and low misidentification rates.

Findings

High muon identification efficiency with low misidentification rate.

Efficiency measurements accurate at per-mille to percent level.

Excellent performance across wide momentum and detector acceptance.

Abstract

This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 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 $Z\to\mu\mu$ and $J/\psi\to\mu\mu$ 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 $|\eta|<2.7$.