Measuring QCD Splittings with Invertible Networks
High Energy Physics - Phenomenology
2021-06-02 v2
Abstract
QCD splittings are among the most fundamental theory concepts at the LHC. We show how they can be studied systematically with the help of invertible neural networks. These networks work with sub-jet information to extract fundamental parameters from jet samples. Our approach expands the LEP measurements of QCD Casimirs to a systematic test of QCD properties based on low-level jet observables. Starting with an toy example we study the effect of the full shower, hadronization, and detector effects in detail.
Cite
@article{arxiv.2012.09873,
title = {Measuring QCD Splittings with Invertible Networks},
author = {Sebastian Bieringer and Anja Butter and Theo Heimel and Stefan Höche and Ullrich Köthe and Tilman Plehn and Stefan T. Radev},
journal= {arXiv preprint arXiv:2012.09873},
year = {2021}
}
Comments
25 pages, 11 figures