2023/10/26 by Wang, Daohan, Cho, Jin-Hwan, Kim, Jinheung +3
#FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph)
paper · doi:10.48550/arxiv.2310.17741
In this study, we explore the phenomenological signatures associated with a light fermiophobic Higgs boson, h\rm f, within the type-I two-Higgs-doublet model at the HL-LHC. Our meticulous parameter scan illuminates an intriguing mass range for m_h\rm f, spanning [1,10] \rm GeV. This mass range owes its viability to substantial parameter points, largely due to the inherent challenges of detecting the soft decay products of h\rm f at contemporary high-energy colliders. Given that this light h\rm f ensures Br(h\rm f→γγ)≃ 1, Br(H^± → h\rm f W^±)≃ 1, and MH^±\lesssim 330 \rm GeV, we propose a golden discovery channel: pp→ h\rm fH^±→ γγγγ l^±ν, where l^± includes e^± and μ^±. However, a significant obstacle arises as the two photons from the h\rm f decay mostly merge into a single jet due to their proximity within ΔR<0.4. This results in a final state characterized by two jets, rather than four isolated photons, thus intensifying the QCD backgrounds. To tackle this, we devise a strategy within Delphes to identify jets with two leading subparticles as photons, termed diphoton jets. Our thorough detector-level simulations across 18 benchmark points predominantly show signal significances exceeding the 5σ threshold at an integrated luminosity of 3 \rm ab-1. Furthermore, our approach facilitates accurate mass reconstructions for both m_h\rm f and MH^±. Notably, in the intricate scenarios with heavy charged Higgs bosons, our application of machine learning techniques provides a significant boost in significance.