2 papers
hep-ex2025
Uncertainty Quantification and Propagation for ACORN, a geometric deep learning tracking pipeline for HEP experiments
Lukas Péron, Paolo Calafiura, Xiangyang Ju +1
We have developed an Uncertainty Quantification process for multistep pipelines and applied it to the ACORN particle tracking pipeline. All our experiments are made using the Track…
physics.data-an2025
Physics and Computing Performance of the EggNet Tracking Pipeline
Jay Chan, Brandon Wang, Paolo Calafiura
Particle track reconstruction is traditionally computationally challenging due to the combinatorial nature of the tracking algorithms employed. Recent developments have focused on…