Papers › Probing Light Fermiophobic Higgs Boson via diphoton jets at the HL-LHC
Probing Light Fermiophobic Higgs Boson via diphoton jets at the HL-LHC
Daohan Wang, Jin-Hwan Cho, Jinheung Kim, Soojin Lee, Prasenjit Sanyal, Jeonghyeon Song
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In this study, we explore the phenomenological signatures associated with a light fermiophobic Higgs boson, h_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_f), spanning [1,10] 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_f at contemporary high-energy colliders. Given that this light h_f ensures Br(h_f→γγ)≃1, Br(H^± →h_f W^±)≃1, and M_(H^±)≲330 GeV, we propose a golden discovery channel: pp→h_fH^±→γγγγ l^±ν, where l^± includes e^± and μ^±. However, a significant obstacle arises as the two photons from the h_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 \textsc{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 ab⁻¹. Furthermore, our approach facilitates accurate mass reconstructions for both m_(h_f) and M_(H^±). Notably, in the intricate scenarios with heavy charged Higgs bosons, our application of machine learning techniques provides a significant boost in significance.
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