Graph Neural Networks for Charged Particle Tracking on FPGAs

Graph Neural Networks for Charged Particle Tracking on FPGAs

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) a...

Full description

Bibliographic Details
Main Authors: Atkinson, M. (Author), DeZoort, G. (Author), Duarte, J. (Author), Elabd, A. (Author), Elmer, P. (Author), Hauck, S. (Author), Hsu, S.-C (Author), Hu, J.-X (Author), Huang, S.-Y (Author), Lai, B.-C (Author), Neubauer, M. (Author), Ojalvo, I. (Author), Razavimaleki, V. (Author), Thais, S. (Author), Trahms, M. (Author)
Format: Article
Language:English
Published: Frontiers Media S.A. 2022
Subjects:
FPGAs
graph neural networks
LHC
tracking
trigger
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items