Abstract
In this paper we probe inert Higgs doublet model at the LHC using Vector Boson Fusion (VBF) search strategy. We optimize the selection cuts and investigate the parameter space of the model and we show that the VBF search has a better reach when compared with the monojet searches. We also investigate the Drell-Yan type cuts and show that they can be important for smaller charged Higgs masses. We determine the $3\sigma$ reach for the parameter space using these optimized cuts for a luminosity of 3000 fb$^{-1}$.
Highlights
The particle physics origin of 27% of the Universe is still unknown
If the signals from a particular physics model which possess a dark matter (DM) candidate are discovered at the laprgffiffie hadron collider (LHC), we would be able to establish that model but it would give us an opportunity to investigate the cosmology in the pre-big bang nucleosynthesis (BBN) era
We find that larger values of MHÆ and λL produce larger significance for vector boson fusion (VBF) analysis due to large production cross sections
Summary
The particle physics origin of 27% of the Universe is still unknown. The results from the direct, indirect detections and the collider experiment are investigating particle physics models which provide a dark matter candidate. There can be multiple DM candidates (e.g., axion and DM from the inert doublet model) and in such scenarios [28,29], the direct and indirect detection cross sections should be reduced by R and R2 respectively with R ≡ Ωh2=0.12 From all these considerations, it appears that the search at the LHC should be strategized without applying restrictions arising from the thermal annihilation rate and the direct and indirect detection constraints. If the signals from a particular physics model which possess a DM candidate are discovered at the LHC, we would be able to establish that model but it would give us an opportunity to investigate the cosmology in the pre-BBN era Following this strategy, the monojet final state has been used effectively to search for parameter space of this model in Ref.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have