Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles. Three published neural network-based shower separation models...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Lai, S, Utehs, J, Wilhahn, A, Fouz, M. C, Bach, O, Brianne, E, Ebrahimi, A, Gadow, K, Göttlicher, P, Hartbrich, O, Heuchel, D, Irles, A, Krüger, K, Kvasnicka, J, Lu, S, Neubüser, C, Provenza, A, Reinecke, M, Sefkow, F, Schuwalow, S, De Silva, M, Sudo, Y, Tran, H. L, Liu, L, Masuda, R, Murata, T, Ootani, W, Seino, T, Takatsu, T, Tsuji, N, Pöschl, R, Richard, F, Zerwas, D, Hummer, F, Simon, F, Boudry, V, Brient, J-C, Nanni, J, Videau, H, Buhmann, E, Garutti, E, Huck, S, Kasieczka, G, Martens, S, Rolph, J, Wellhausen, J, Bilki, B, Northacker, D, Onel, Y, Emberger, L, Graf, C
Format:	Artikel
Sprache:	eng
Schlagworte:	Physics - Instrumentation and Detectors
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!