Karlsruhe 2024 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 39: Detectors 4 (calorimeters)
T 39.7: Vortrag
Dienstag, 5. März 2024, 17:30–17:45, Geb. 30.23: 2/1
Reconstruction of test beam data for the CheapCal prototype detector using Machine Learning — Alessia Brignoli1, Andrew Picot Conaboy1, Valery Dormenev2, Christian Dreisbach3, Karl Eichhorn3, Jan Friedrich3, Heiko Markus Lacker1, Martin J. Losekamm3, Anupama Reghunath1, •Christian Scharf1, Ben Skodda1, Valerian von Nicolai1, Ida Wöstheinrich1, and Hans-Georg Zaunick2 — 1Humboldt-Universität zu Berlin — 2Justus-Liebig-Universität Gießen — 3Technische Universität München
The CheapCal prototype detector is an extruded plastic scintillator detector with wavelength-shifting (WLS) fibers embedded in perpendicular grooves on the front and the back of the 25 × 25 cm2 scintillator plate. The WLS fibers are read out on both ends by Silicon Photomultipliers. Due to the short light attenuation length of the scintillator material, photons couple only to the nearest WLS fibers, allowing for reconstruction of the positions of passing particles.
We will present the reconstruction of 100 GeV muon test beam data using Machine Learning. The impact of different read-out schemes on the position resolution of the detector will be evaluated.
We acknowledge the support from BMBF via the High-D consortium.
Keywords: SiPM; Scintillators; Calorimeters; Test Beam; Machine Learning