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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.17854 |
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Table of Contents:
- A model based on a $U(1)_{T^3_R}$ extension of the Standard Model can address the mass hierarchy between generations of fermions, explain thermal dark matter abundance, and the muon $g - 2$, $R_{(D)}$, and $R_{(D^*)}$ anomalies. The model contains a light scalar boson $ϕ'$ and a heavy vector-like quark $χ_\mathrm{u}$ that can be probed at CERN's Large Hadron Collider (LHC). We perform a phenomenology study on the production of $ϕ'$ and $χ_u$ particles from proton-proton $(\mathrm{pp})$ collisions at the LHC at $\sqrt{s}=13.6$ TeV, primarily through $g{-g}$ and $t{-χ_\mathrm{u}}$ fusion. We work under an effective field theory approach, in which the $χ_\mathrm{u}$ and $ϕ'$ masses are free parameters. We perform a phenomenological analysis considering $χ_\mathrm{u}$ final states to b-quarks, muons, and neutrinos, and $ϕ'$ decays to $μ^+μ^-$. A machine learning algorithm is used to maximize the signal sensitivity, considering an integrated luminosity of $3000$ $\textrm{fb}^{-1}$. The proposed methodology can be a key mode for discovery over a large mass range, including low masses, traditionally considered difficult due to experimental constraints.