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

Area of Science:

• High Energy Physics
• Particle Physics
• Detector Technology

Background:

• The Large Hadron Collider's (LHC) increased center-of-mass energy to 13 TeV for Run 2 enhances the study of dense environments within high-energy jets.
• Such environments are crucial for new physics searches and Standard Model measurements, characterized by fine charged-particle separations.
• Tracking detector performance is critical for analyzing these complex collision events.

Purpose of the Study:

• To investigate the impact of charged-particle separations and multiplicities on track reconstruction performance in high-transverse-momentum jets.
• To quantify the track reconstruction efficiency within the cores of jets using a novel data-driven method.
• To assess the performance of the ATLAS experiment's tracking detectors at 13 TeV.

Main Methods:

• Comparison of basic track quantities between 3.2 fb⁻¹ of ATLAS data and simulations of proton-proton collisions at 13 TeV.
• Utilized a novel, data-driven method employing energy loss (dE/dx) to identify pixel clusters from two charged particles.
• Analyzed jet transverse momenta ranging from 200 to 1600 GeV.

Main Results:

• The study discusses the influence of particle density and separation on track reconstruction.
• A data-driven method was developed to measure reconstruction efficiency in jet cores.
• The fraction of charged particles missed by reconstruction was found to be 1.7% for 200-400 GeV jets and 2.8% for 1400-1600 GeV jets.

Conclusions:

• The track reconstruction performance in dense jet environments was successfully quantified.
• The novel method provides valuable insights into detector performance in challenging conditions.
• Understanding reconstruction inefficiencies is vital for precision measurements and searches at the LHC.