Pinning down the leptophobic $Z^\prime$ in leptonic final states with Deep Learning

TL;DR

This paper employs Deep Learning to analyze leptophobic $Z'$ bosons and right-handed neutrinos at the LHC, identifying parameter regions accessible via monolepton final states beyond traditional dijet searches.

Contribution

It introduces a Deep Learning approach to detect leptophobic $Z'$ and right-handed neutrinos in monolepton channels, extending search capabilities at the HL-LHC.

Findings

Deep Learning enhances detection sensitivity for $Z'$ in monolepton channels.

Parameter regions inaccessible to dijet searches can be probed.

Analysis covers six GUT embeddings and a GS benchmark.

Abstract

A leptophobic $Z^\prime$ that does not couple with the Standard Model leptons can evade the stringent bounds from the dilepton-resonance searches. In our earlier paper [T. Arun et al., Search for the $Z'$ boson decaying to a right-handed neutrino pair in leptophobic $U(1)$ models, Phys. Rev. D, 106 (2022) 095035; arXiv:2204.02949], we presented two gauge anomaly-free $U(1)$ models -- one based on the Green-Schwarz (GS) anomaly cancellation mechanism, and the other on a grand unified theory (GUT) framework with gauge kinetic mixing -- where a heavy leptophobic $Z'$ is present along with right-handed neutrinos ($N_R$). We pointed out the interesting possibility of a correlated search for $Z'$ and $N_R$ at the LHC through the $pp\to Z'\to N_R N_R$ channel. This channel can probe a part of the $Z'$ parameter space beyond the reach of the standard dijet resonance searches. In this follow-up paper, we analyse the challenging monolepton final state arising from the decays of the $N_R$ pair with Deep Learning. We present the high-luminosity LHC discovery reaches for six different GUT embeddings and a benchmark point in the GS setup. We also update our previous estimates in the dilepton channel with Deep Learning. We identify parameter regions that can be probed with the proposed channel but will remain inaccessible to dijet searches at the HL-LHC.