Jul 10 – 22, 2023
Orthodox Academy of Crete, Kolymbari, Crete, Greece (Hybrid mode)
Europe/Athens timezone

Probing a MeV-scale Scalar Boson and a TeV-Scale Vector-like Quark in the $U(1)_{T3R}$ BSM Extension from $gg$ Fusion, $qq$ Fusion at the LHC using Machine Learning

Jul 12, 2023, 5:00 PM
20m
Room 1

Room 1

Talk High Energy Particle Physics High Energy Particle Physics

Speaker

Umar Sohail Qureshi (Vanderbilt University)

Description

The $U(1)_{T 3R}$ extension of the Standard Model is an attractive formulation that addresses the mass hierarchy between the third and the first two generations of fermions, explains thermal dark matter abundance, and the muon $g - 2$ and $R_{K^{(*)}}$ anomalies. The model contains a dark matter candidate scalar boson, the $\phi$ particle, and a vector-like quark (a scalar and vector mediator), the $\chi_u$ particle. We perform a phenomenological study to search for and constrain the parameter space of the $\chi_u$ and $\phi$ particles.
In particular, we present a study looking at the production of $\phi$ and ${\chi}_u$ particles from proton-proton $(pp)$ collisions at CERN’s Large Hadron Collider (LHC) primarily through gluon-gluon and quark-quark fusion. We consider the final states of the $\chi_u$ decaying to $b$-quarks, muons, and neutrinos and the $\phi$ particle decaying to $\mu^+\mu^-$. We use machine learning algorithms to maximize the signal sensitivity and aim for a $\ge 5\sigma$ discovery reach with an integrated luminosity of 3000 fb$^{-1}$. Further, we note 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.

Details

Umar Sohail Qureshi, Vanderbilt University, USA.

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Authors

Alfredo Gurrola (Vanderbilt University (US)) Umar Sohail Qureshi (Vanderbilt University)

Presentation materials