Understanding two same-sign and three leptons with $b$-jets in four top quark events at the LHC

TL;DR

This paper investigates the production of multi-lepton final states with $b$-jets in four top quark events at the LHC, aiming to distinguish between Standard Model and beyond Standard Model mechanisms using machine learning.

Contribution

It introduces a machine learning approach to differentiate SM and BSM four top quark production mechanisms based on kinematic variables.

Findings

Machine learning can effectively distinguish SM from BSM four top production.

Analysis of kinematic variables reveals key differences in production mechanisms.

Results support the potential for new physics searches in multi-lepton final states.

Abstract

The top quark is the heaviest known elementary particle of the Standard Model (SM) of particle physics and, therefore, it is expected to have large couplings to hypothetical new physics in many models beyond the SM (BSM). Various studies have predicted the presence of multi-lepton anomalies at the LHC. One of those anomalies is the excess production of two same-sign leptons and three isolated leptons in association with $b$-jets. These are reasonably well described by a 2HDM+$S$ model, where $S$ is a singlet scalar. Both the ATLAS and CMS experiments have reported sustained excesses in these final states. This includes corners of the phase-space where production of top quark pairs in association with a $W$ boson contributes to. Here, we investigate the production of two same-sign and three leptons from the production of four top quark final states. Our focus is on understanding the differences between the SM and BSM production mechanisms of four top quarks from $t\overline{t} A$ ($A \rightarrow t\overline{t}$) using Machine Leaning techniques with twelve discriminating kinematic variables.