Graph Neural Networks for Charged Particle Tracking on FPGAs. (arXiv:2112.02048v2 [physics.ins-det] UPDATED)

The determination of charged particle trajectories in collisions at the CERN
Large Hadron Collider (LHC) is an important but challenging problem, especially
in the high interaction density conditions expected during the future
high-luminosity phase of the LHC (HL-LHC). Graph neural networks (GNNs) are a
type of geometric deep learning algorithm that has successfully been applied to
this task by embedding tracker data as a graph -- nodes represent hits, while
edges represent possible track segments -- and classifying the edges …

arxiv graph graph neural networks networks neural networks physics tracking