An Object Condensation Pipeline for Charged Particle Tracking at the High Luminosity LHC
Kilian Lieret,
Gage DeZoort
Abstract:Recent work has demonstrated that graph neural networks (GNNs) trained for charged particle tracking can match the performance of traditional algorithms while improving scalability to prepare for the High Luminosity LHC experiment. Most approaches are based on the edge classification (EC) paradigm, wherein tracker hits are connected by edges, and a GNN is trained to prune edges, resulting in a collection of connected components representing tracks. These connected components are usually collected by a clusteri… Show more
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