Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers

Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers

This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar reconstruction tasks in the LHC. In this paper, a...

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Hlavní autoři: Hewes Jeremy, Aurisano Adam, Cerati Giuseppe, Kowalkowski Jim, Lee Claire, Liao Wei-keng, Day Alexandra, Agrawal Ankit, Spiropulu Maria, Vlimant Jean-Roch, Gray Lindsey, Klijnsma Thomas, Calafiura Paolo, Conlon Sean, Farrell Steve, Ju Xiangyang, Murnane Daniel
Médium: Článek
Jazyk:English
Vydáno: EDP Sciences 2021-01-01
Edice:EPJ Web of Conferences
On-line přístup:https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03054.pdf

Internet

https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03054.pdf

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