Software Compensation for Highly Granular Calorimeters using Machine Learning

Software Compensation for Highly Granular Calorimeters using Machine Learning

A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2024-03
Hauptverfasser: Lai, S, Utehs, J, Wilhahn, A, Bach, O, Brianne, E, Ebrahimi, A, Gadow, K, Göttlicher, P, Hartbrich, O, Heuchel, D, Irles, A, Krüger, K, Kvasnicka, J, S Lu, Neubüser, C, Provenza, A, Reinecke, M, Sefkow, F, Schuwalow, S, De Silva, M, Sudo, Y, Tran, H L, Buhmann, E, Garutti, E, Huck, S, Kasieczka, G, Martens, S, Rolph, J, Wellhausen, J, Blazey, G C, Dyshkant, A, Francis, K, Zutshi, V, Bilki, B, Northacker, D, Onel, Y, Hummer, F, Simon, F, Kawagoe, K, Onoe, T, Suehara, T, Tsumura, S, Yoshioka, T, Fouz, M C, Emberger, L, Graf, C, Wagner, M, Pöschl, R, Richard, F, Zerwas, D, Boudry, V, J-C Brient, Nanni, J, Videau, H, Liu, L, Masuda, R, Murata, T, Ootani, W, Takatsu, T, Tsuji, N, Chadeeva, M, Danilov, M, Korpachev, S, Rusinov, V
Format: Artikel
Sprache:eng
Schlagworte:
Compensation
Control methods
Machine learning
Neural networks
Particle energy
Software
Weighting
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied.
ISSN:2331-8422