3 papers
hep-ex2025
Exploring DHCAL design and performance with Graph Neural Networks
M. Borysova, D. Zavazieva, N. Kakati +2
In the context of a gas-sampling Digital Hadronic Calorimeter (DHCAL), we explore the potential of using Graph Neural Networks (GNN) for hadron energy reconstruction and Particle I…
hep-ph2025
Point Cloud Deep Learning Methods for Particle Shower Reconstruction in the DHCAL
Maryna Borysova, Shikma Bressler, Eilam Gross +2
Precision measurement of hadronic final states presents complex experimental challenges. The study explores the concept of a gaseous Digital Hadronic Calorimeter (DHCAL) and discus…
physics.ins-det2024
Design and optimization of a hadronic calorimeter based on micropattern gaseous detectors for a future experiment at the Muon Collider
Antonello Pellecchia, Marco Buonsante, Maryna Borysova +14
Micro-pattern gaseous detectors (MPGDs) are a promising readout technology for hadronic calorimeters (HCAL) thanks to their good space resolution, longevity and rate capability. We…