2 papers
quant-ph2026
Optimization-based Unfolding in High-Energy Physics
Simone Gasperini, Gianluca Bianco, Marco Lorusso +2
In experimental High-Energy Physics, unfolding refers to the problem of estimating the underlying distribution of a physical observable from detector-level data, in the presence of…
hep-ex2024
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…