Abstract
Distinguishing quarks from gluons based on low-level detector output
is one of the most challenging applications of multi-variate and machine
learning techniques at the LHC. We first show the performance of our
4-vector-based LoLa tagger without and after considering detector
effects. We then discuss two benchmark applications, mono-jet searches
with a gluon-rich signal and di-jet resonances with a quark-rich signal.
In both cases an immediate benefit compared to the standard event-level
analysis exists.
Funder
Baden-Württemberg Stiftung
Deutsche Forschungsgemeinschaft
Subject
General Physics and Astronomy
Cited by
45 articles.
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