3 papers
hep-ph2026
Enabling stable preservation of ML algorithms in high-energy physics with petrifyML
Andy Buckley, Louie Corpe, Martin Habedank +1
Machine learning (ML) in high-energy physics (HEP) has moved in the LHC era from an internal detail of experiment software, to an unavoidable public component of many physics data…
hep-ex2026
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…
hep-ph2025
Constraints On New Theories Using Rivet : CONTUR version 3 release note
Andy Buckley, Jon Butterworth, Joseph Egan +7
The CONTUR toolkit exploits RIVET and its library of more than a thousand energy-frontier differential cross-section measurements from the Large Hadron Collider to allow rapid limi…