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.
Highlights
Background efficienciesεB are defined as relative to the number of those fat jets
We reduce the size of the fat jet in steps of ∆R = 0.1 and compute the corresponding values of mrec(R)
We demonstrated how the updated HEPTopTagger2 performs in searches for Z bosons or other heavy resonances decaying to top pairs in the upcoming LHC run
Summary
The key challenge of any top tagger is its broad range of applications and the related optimization of the algorithms and codes. The improvement from the transverse momentum spectra is shown in the left panel of figure 1 All this illustrates that the kinematic information on the tagged and reconstructed tops can increase the background rejection by 50% to 100% for fixed signal tagging efficiency. Final-state radiation (FSR) turns one of the key advantages of our top tagger into a significant problem: unlike some other top tagging approaches, the HEPTopTagger returns the 4-momentum of the tagged top, including a cut on the reconstructed top mass mrec ∈ [150, 200] GeV [35]. Reconstructed mass distribution of the Z signal and the backgrounds based on the tagged tops (left) and the corresponding filtered fat jets (right). The analysis based on the set of kinematic variables shown in eq (2.4) gives us an improvement of up to a factor 5 in background rejection for a constant Z -signal efficiency
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