We present a method for diagnostics analysis for pixelated particle detectors. The method is based on extracting information from the detector in the form of model parameters by using a representative mathematical model. To illustrate the procedure we analyzed real experimental data obtained with the electromagnetic calorimeter ECAL2 of the COMPASS experiment at CERN. Having observed the data, the typical pulses were fitted with a mathematical model. Heat maps were drawn to visualize the distribution of the mean values of each of the fitted parameters. This data visualization technique is useful for highlighting areas with similar behavior and detecting abnormal responses in single cells. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG

Diagnostic Analytics for Pixelated Particle Detectors: A Case Study / Florian Samayoa, W., Valinoti, B., Molina, R., Garcia, L.G., Crespo, M.L., Carrato, S., Cicuttin, A., Levorato, S.. - 1036 LNEE:(2023), pp. 216-221. (APPLEPIES 2022 Genova September 6 to 8, 2023) [10.1007/978-3-031-30333-3_28].

Diagnostic Analytics for Pixelated Particle Detectors: A Case Study

Florian Samayoa W.
Primo
;
Valinoti B.
Secondo
;
Molina R.;Garcia L. G.;Carrato S.;
2023-01-01

Abstract

We present a method for diagnostics analysis for pixelated particle detectors. The method is based on extracting information from the detector in the form of model parameters by using a representative mathematical model. To illustrate the procedure we analyzed real experimental data obtained with the electromagnetic calorimeter ECAL2 of the COMPASS experiment at CERN. Having observed the data, the typical pulses were fitted with a mathematical model. Heat maps were drawn to visualize the distribution of the mean values of each of the fitted parameters. This data visualization technique is useful for highlighting areas with similar behavior and detecting abnormal responses in single cells. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG
2023
9783031303326
9783031303333
978-3-031-30335-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3120026
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