337 citations · 2.6k across the 40 of their papers we have counts for
41 papers
Model-independent search for the presence of new physics in events including with = 13 TeV pp data recorded by the ATLAS detector at the LHC
ATLAS Collaboration
A model-independent search for new physics leading to final states containing decays is performed with 139 fb of = 13 TeV pp collision data recor…
Reconstruction of Large Radius Tracks with the Exa.TrkX pipeline
Chun-Yi Wang, Xiangyang Ju, Shih-Chieh Hsu +22
Particle tracking is a challenging pattern recognition task at the Large Hadron Collider (LHC) and the High Luminosity-LHC. Conventional algorithms, such as those based on the Kalm…
Accelerating the Inference of the Exa.TrkX Pipeline
Alina Lazar, Xiangyang Ju, Daniel Murnane +21
Recently, graph neural networks (GNNs) have been successfully used for a variety of particle reconstruction problems in high energy physics, including particle tracking. The Exa.Tr…
Graph Neural Networks for Charged Particle Tracking on FPGAs
Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang +12
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…
A search for the decays of stopped long-lived particles at TeV with the ATLAS detector
ATLAS Collaboration
A search for long-lived particles, which have come to rest within the ATLAS detector, is presented. The subsequent decays of these long-lived particles can produce high-momentum je…
Charged particle tracking via edge-classifying interaction networks
Gage DeZoort, Savannah Thais, Javier Duarte +5
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high energ…