Heidelberg 2022 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 16: Experimental Methods (general) 1
T 16.2: Vortrag
Montag, 21. März 2022, 16:30–16:45, T-H29
Clustering and tracking in dense environments with the ITk — •Nicola de Biase — DESY Hamburg
Dense hadronic environments, encountered in particular in the core of high-pT jets or hadronic τ decays, present specific challenges for the reconstruction of charged-particle trajectories (tracks) in the ATLAS silicon-pixel tracking detector, as the charge clusters left by different ionising particles in the silicon sensors can merge with a sizeable rate. Tracks competing for the same cluster are penalised for sharing it, leading to a loss in tracking efficiency.
In the current ATLAS Inner Detector, a machine learning algorithm is used for classifying and splitting merged clusters with minimal efficiency losses, leading to better performances of Clustering and Tracking in Dense Environments (CTIDE). The new Inner Tracker (ITk), which will replace the current Inner Detector as part of the ATLAS phase-2 upgrade, will benefit from an improved granularity thanks to its smaller pixel sensor size, which might render such a procedure unnecessary.
In this talk, the expected performance of the ITk in dense environments will be discussed, addressing the question of whether a cluster splitting procedure is necessary.