Quark-versus-gluon tagging in CMS Open Data with CWoLa and TopicFlow

Abstract We use the CMS Open Data to examine the performance of weakly-supervised learning for tagging quark and gluon jets at the LHC. We target Z+jet and dijet events as respective quark- and gluon-enriched mixtures and derive samples both from data taken in 2011 at 7 TeV, and from Monte Carlo. CW...

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Bibliographic Details
Main Authors: Matthew J. Dolan, John Gargalionis, Ayodele Ore
Format: Article
Language:English
Published: SpringerOpen 2025-08-01
Series:Journal of High Energy Physics
Subjects:
Online Access:https://doi.org/10.1007/JHEP08(2025)024
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