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20 April 2024

» arxiv » 1902.8276

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End-to-End Jet Classification of Quarks and Gluons with the CMS Open Data
Michael Andrews ; John Alison ; Sitong An ; Patrick Bryant ; Bjorn Burkle ; Sergei Gleyzer ; Meenakshi Narain ; Manfred Paulini ; Barnabas Poczos ; Emanuele Usai ;
Date:	21 Feb 2019
Abstract:	We describe the construction of end-to-end jet image classifiers based on simulated low-level detector data to discriminate quark- vs. gluon-initiated jets with high-fidelity simulated CMS Open Data. We highlight the importance of precise spatial information and demonstrate competitive performance to existing state-of-the-art jet classifiers. We further generalize the end-to-end approach to event-level classification of quark vs. gluon di-jet QCD events. We compare the fully end-to-end approach to using hand-engineered features and demonstrate that the end-to-end algorithm is robust against the effects of underlying event and pile-up.
Source:	arXiv, 1902.8276
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