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

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, $${\text { d}}{} \textit{E}/d\textit{x}$$ , 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 $$0.061 \pm 0.006\ {\text {(stat.)}} \pm 0.014\ {\text {(syst.)}}$$ and $$0.093 \pm 0.017\ {\text {(stat.)}}\pm 0.021\ {\text {(syst.)}}$$ for jet transverse momenta of 200–400  $$\text {GeV}$$ and 1400–1600  $$\text {GeV}$$ , respectively.