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2024-11-22 2:13

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Conference: Bucharest University Faculty of Physics 2024 Meeting

Section: Theoretical and Computational Physics, High-Energy Physics, Applied Mathematics

Title:

Rate of Fake Tracks in Dense Environments Using Run3 Data in the ATLAS Experiment

Authors:

Matei-Stefan Filip (1,2), Otilia Ducu (1,2), Julien Maurer (1,2)

^*
Affiliation:

1) IFIN-HH, Particle Physics Department, Reactorului 30, RO-077125, Măgurele-Bucharest, Romania

2) Faculty of Physics, University of Bucharest, Atomiștilor 405, RO-077125, Măgurele-Bucharest, Romania

E-mail

matei.filip@cern.ch

Keywords:

Fake Tracks, Jet Core, ATLAS Detector

Abstract:

The Large Hadron Collider (LHC) along with its upcoming High Luminosity upgrade, will continue to drive particle physics research in the next decade, probing fundamental properties of matter and interactions at unprecedented energies. This study focuses on understanding charged particle trajectories within hadronic jets, crucial for unraveling complex quantum chromodynamics processes. Jets, collimated streams of hadrons, are reconstructed from calorimetric data, augmented by trajectory information from the Inner Detector. Additionally, "particle flow" [1] methods are employed in order to enhance jet reconstruction efficiency by leveraging data from the entire detector system. However, reconstructing trajectories within high-momentum jets presents challenges, including increased misreconstruction rates due to overlapping tracks and experimental noise [2, 3]. Fake tracks, originating from nearly collinear tracks within jet cores and random overlapping tracks, contribute significantly to misreconstruction rates, especially in highdensity environments. To estimate the rate of fake tracks in real data, we rely on the agreement between Monte Carlo (MC) simulation results and physical data acquired by the ATLAS detector in Run3 in order to employ a fitting approach utilized in a control region enriched with fake tracks. This is further aided by dedicated studies utilizing MC simulations to discern variables capable of discriminating fake tracks such as the number of Semiconductor tracker hits and holes. The choice is guided by the quality of the modelling of such variables when compared with collision data. These fit results are then extrapolated to the pre-selection region in order for us to present the final uncertainty value in the rate of fake tracks.

References:

[1] ATLAS Collaboration, Jet reconstruction and performance using particle flow with the ATLAS Detector, Eur.Phys.J.C 77 (2017) 466, [hepex:1703.10485]

[2] ATLAS Collaboration, Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2, Eur.Phys.J.C 77 (2017) 673, [hep-ex:1704.07983]

[3] ATLAS Collaboration, Modelling of Track Reconstruction Inside Jets with the 2016 ATLAS √s=13 TeV pp Dataset, (2017) ATL-PHYS-PUB-2017-016, https://cds.cern.ch/record/2275639

Acknowledgement:

This study was supported by PN23210104 and ATLAS CERN-RO projects.