Gießen 2024 – scientific programme

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HK: Fachverband Physik der Hadronen und Kerne

HK 56: Heavy-Ion Collisions and QCD Phases XIV

HK 56.1: Talk

Wednesday, March 13, 2024, 17:30–17:45, HBR 62: EG 05

Photon reconstruction in the Transition Radiation Detector of ALICE — •Peter Stratmann for the ALICE Germany collaboration — Universität Münster

The Transition Radiation Detector (TRD) of the ALICE detector at the Large Hadron Collider has the main purpose of identifying electrons and triggering on electrons and jets. Furthermore, it improves the resolution in track reconstruction at high transverse momenta. The working principle is based on transition radiation, which is produced by charged particles transversing boundaries of material with different dielectric constants.

In a rather new approach, the TRD should be used for measuring the photon production through the detection of conversion electrons. This is facilitated by the large material budget located in front and inside of the TRD. For this purpose, stand-alone tracking independent of the Inner Tracking System and the Time Projection Chamber had already been implemented. So far, this is achieved by a Kalman filter. As a new method, the photons are reconstructed in the TRD using Graph Neural Networks. These have the advantage that they operate well on the high-dimensional and sparse nature presented by the TRD data. In this talk, we will present the principles of the TRD, the direct photon reconstruction in the stand-alone tracking, and first results obtained with the Graph Neural Network.

Supported by BMBF within the ERuM framework, and the DFG as part of the GRK 2149.

Keywords: ALICE; Photon reconstruction; Graph Neural Networks