Resonance Searches with an Updated Top Tagger
Gregor Kasieczka, Tilman Plehn, Torben Schell, Thomas Strebler, Gavin, P. Salam
TL;DR
This paper introduces an improved top tagger for resonance searches at the LHC, significantly enhancing background rejection by utilizing additional variables and advanced analysis techniques.
Contribution
The paper presents HEPTopTagger2, a new top tagging algorithm with optimized parameters and features for better performance in LHC resonance searches.
Findings
Background rejection improved by up to a factor of 30.
Increased set of variables enhances tagger performance.
New tagger released for upcoming LHC run.
Abstract
The performance of top taggers, for example in resonance searches, can be significantly enhanced through an increased set of variables, with a special focus on final-state radiation. We study the production and the decay of a heavy gauge boson in the upcoming LHC run. For constant signal efficiency, the multivariate analysis achieves an increased background rejection by up to a factor 30 compared to our previous tagger. Based on this study and the documentation in the Appendix we release a new HEPTopTagger2 for the upcoming LHC run. It now includes an optimal choice of the size of the fat jet, N-subjettiness, and different modes of Qjets.
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