Machine learning-enhanced search for a vectorlike singlet $B$ quark decaying to a singlet scalar or pseudoscalar

TL;DR

This paper develops a machine learning-based search strategy for detecting vectorlike B quarks decaying into a scalar or pseudoscalar, enhancing sensitivity to new decay modes at the high-luminosity LHC.

Contribution

It introduces a neural network approach to improve detection of B quark decays involving a new scalar or pseudoscalar, expanding search capabilities beyond traditional methods.

Findings

Neural network significantly improves signal-background separation.

Large regions of parameter space are discoverable with the proposed method.

The approach enhances sensitivity in the monolepton channel.

Abstract

The presence of a new decay mode relaxes the current mass exclusion limits on vectorlike quarks considerably. We consider the case of a weak-singlet vectorlike $B$ quark that can decay to a singlet scalar or pseudoscalar $\Phi$. In an earlier paper [A. Bhardwaj et al., Roadmap to explore vectorlike quarks decaying to a new scalar or pseudoscalar, Phys. Rev. D, 106 (2022) 095014; arXiv:2203.13753], we mapped the possibilities to explore such setups at the LHC. We showed that it is possible for a $B$ quark to decay into $\Phi$ and the $\Phi$ to dominantly decay to a pair of gluons or $b$ quark(s) without fine-tuning the parameters. In this paper, we present a collider search strategy to look for the pair production of singlet $B$ quarks. If both $B$ quarks decay into $b\Phi$ pairs, the final state is fully hadronic: $B{B}\to(b\Phi)({b}\Phi)\to (bgg)({b}gg)/(bb{b})({b}b{b})$, which is very challenging to probe. Therefore, we consider a simpler mixed decay specific to the singlet $B$ case, $BB\to(b\Phi)(tW)$ with a lepton in the final state, to achieve the best sensitivity at the high-luminosity LHC. We use a deep neural network with a weighted cross-entropy loss to separate the signal from the huge SM background. Our analysis shows that large areas of the $M_{B}-M_{\Phi}$ parameter space are discoverable through this signature. We show how the discovery and exclusion regions scale with the branching ratio in the new decay mode. We also estimate the reach in the inclusive monolepton channel with the same network model.