Track Seeding and Labelling with Embedded-space Graph Neural Networks

To address the unprecedented scale of HL-LHC data, the Exa.TrkX project is investigating a variety of machine learning approaches to particle track reconstruction. The most promising of these solutions, graph neural networks (GNN), process the event as a graph that connects track measurements (detec...

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Veröffentlicht in:	arXiv.org 2020-06
Hauptverfasser:	Choma, Nicholas, Murnane, Daniel, Ju, Xiangyang, Calafiura, Paolo, Conlon, Sean, Farrell, Steven, Prabhat, Cerati, Giuseppe, Gray, Lindsey, Klijnsma, Thomas, Kowalkowski, Jim, Spentzouris, Panagiotis, Jean-Roch Vlimant, Spiropulu, Maria, Aurisano, Adam, Hewes, V, Tsaris, Aristeidis, Terao, Kazuhiro, Usher, Tracy
Format:	Artikel
Sprache:	eng
Schlagworte:	Classifiers Clustering Data points Graph neural networks Graph theory Graphical representations Graphs Machine learning Message passing Neural networks Nodes Particle tracking Performance enhancement Post-production processing Sensors
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