5 citations · 12 across the 4 of their papers we have counts for
4 papers
Precision calibration of calorimeter signals in the ATLAS experiment using an uncertainty-aware neural network
ATLAS Collaboration
The ATLAS experiment at the Large Hadron Collider explores the use of modern neural networks for a multi-dimensional calibration of its calorimeter signal defined by clusters of to…
Design of a SiPM-on-Tile ZDC for the future EIC and its Performance with Graph Neural Networks
Ryan Milton, Sebouh J. Paul, Barak Schmookler +5
We present a design for a high-granularity zero-degree calorimeter (ZDC) for the upcoming Electron-Ion Collider (EIC). The design uses SiPM-on-tile technology and features a novel…
The Optimal use of Segmentation for Sampling Calorimeters
Fernando Torales Acosta, Bishnu Karki, Piyush Karande +7
One of the key design choices of any sampling calorimeter is how fine to make the longitudinal and transverse segmentation. To inform this choice, we study the impact of calorimete…
Comparison of Point Cloud and Image-based Models for Calorimeter Fast Simulation
Fernando Torales Acosta, Vinicius Mikuni, Benjamin Nachman +5
Score based generative models are a new class of generative models that have been shown to accurately generate high dimensional calorimeter datasets. Recent advances in generative…