Performance of the ATLAS Track Reconstruction Algorithms in Dense Environments in LHC Run 2 - ATLAS collaboration (2859 authors) (2017)
With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 $\text {TeV}$ 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 $\text {TeV}$ . 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 $\text {GeV}$ is quantified using a novel, data-driven, method. The method uses the energy loss, ${\text { d}}{} E/dx$ , 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 $0.061 ± 0.006\ {\text {(stat.)}} ± 0.014\ {\text {(syst.)}}$ and $0.093 ± 0.017\ {\text {(stat.)}}± 0.021\ {\text {(syst.)}}$ for jet transverse momenta of 200–400 $\text {GeV}$ and 1400–1600 $\text {GeV}$ , respectively.