Abstract
The tracking performance parameters of the ATLAS Transition Radiation Tracker (TRT) as part of the ATLAS inner detector are described in this paper for different data-taking conditions in proton-proton, proton-lead and lead-lead collisions at the Large Hadron Collider (LHC). The performance is studied using data collected during the first period of LHC operation (Run 1) and is compared with Monte Carlo simulations. The performance of the TRT, operating with two different gas mixtures (xenon-based and argon-based) and its dependence on the TRT occupancy is presented. These studies show that the tracking performance of the TRT is similar for the two gas mixtures and that a significant contribution to the particle momentum resolution is made by the TRT up to high particle densities.
Highlights
The Transition Radiation Tracker (TRT) tracking performance at low and high occupancies based on proton-proton, heavy ion and proton-lead collisions during Run 1 of the Large Hadron Collider (LHC) operation is presented
The TRT operation with either a xenon-based or an argon-based gas mixture is studied and similar tracking performance is found for the two gas mixtures
The straw efficiency is found to be larger than 96% and the straw track position measurement accuracy in the straws better than 130 μm in low occupancy conditions
Summary
Simulated events are produced with various Monte Carlo event generators, processed through a full. ATLAS detector simulation [6] using G 4 [7], and reconstructed with the same procedure as for data. For the studies with a Xe-based gas mixture, Z → μμ events, with a μ distribution between 5 and 30, are simulated using the S. For the studies with an Ar-based gas mixture, samples with single muons are used. Muons are generated with η and pT distributions similar to the ones observed in proton-lead collisions in 2013 data. The same conditions for bunch spacing as in data are simulated. The response of the ATLAS detector and the performance of the reconstruction algorithms for heavy-ion collisions are evaluated using simulated minimum-bias events produced with the version 1.38b of the HIJING event generator [10], and using the same bunch-spacing and pile-up conditions as in data. 8.1 [11] generator with parameter values set to the AU2 CT10 tune [12]
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