Probing Light Scalars and Vector-like Quarks at the High-Luminosity LHC

A model based on a $U(1{)}_{T_R^3}$ 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 $R_{(D^{\ast })}$ anomalies. The model contains a light scalar boson ${\phi }^{\mathrm{\prime }}$ and a heavy vector-like quark ${\chi }_{\mathrm{u}}$ that can be probed at CERN’s Large Hadron Collider (LHC). We perform a phenomenology study on the production of ${\phi }^{\mathrm{\prime }}$ and ${\chi }_u$ particles from proton-proton $(\mathrm{p}\mathrm{p})$ collisions at the LHC at $\sqrt{s}=13.6$ TeV, primarily through $g-g$ and $t-{\chi }_{\mathrm{u}}$ fusion. We work under an effective field theory approach, in which the ${\chi }_{\mathrm{u}}$ and ${\phi }^{\mathrm{\prime }}$ masses are free parameters. We perform a phenomenological analysis considering ${\chi }_{\mathrm{u}}$ final states to b-quarks, muons, and neutrinos, and ${\phi }^{\mathrm{\prime }}$ decays to ${\mu }^{+}{\mu }^{-}$. A machine learning algorithm is used to maximize the signal sensitivity, considering an integrated luminosity of $3000$ ${\text{fb}}^{-1}$. 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.