87 citations · 88 across the 4 of their papers we have counts for
5 papers
Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider
Jonathan Renusch, Benjamin Huth, Daniel Murnane +9
We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling task. Kalman filters and linea…
Combined track finding with GNN & CKF
Lukas Heinrich, Benjamin Huth, Andreas Salzburger +1
The application of Graph Neural Networks (GNN) in track reconstruction is a promising approach to cope with the challenges arising at the High-Luminosity upgrade of the Large Hadro…
Machine learning for surface prediction in ACTS
Benjamin Huth, Andreas Salzburger, Tilo Wettig
We present an ongoing R&D activity for machine-learning-assisted navigation through detectors to be used for track reconstruction. We investigate different approaches of training n…
A Common Tracking Software Project
Xiaocong Ai, Corentin Allaire, Noemi Calace +29
The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tunin…
Lattice QCD on a novel vector architecture
Benjamin Huth, Nils Meyer, Tilo Wettig
The SX-Aurora TSUBASA PCIe accelerator card is the newest model of NEC's SX architecture family. Its multi-core vector processor features a vector length of 16 kbits and interfaces…