The mono-Higgs + MET signal at the Large Hadron Collider: a study on the $\gamma\gamma$ and $b\bar{b}$ final states

TL;DR

This paper explores the mono-Higgs plus missing transverse energy channel at the LHC as a promising way to detect scalar dark matter, analyzing both diphoton and b-quark final states with advanced data analysis techniques.

Contribution

It provides a detailed analysis of the mono-Higgs + MET signal for scalar dark matter, including the impact of dimension-6 operators and advanced machine learning methods for signal enhancement.

Findings

Significant improvement in signal detection using Boosted Decision Trees and Neural Networks.

Enhanced sensitivity in the b-quark decay channel compared to traditional cut-based methods.

Dimension-6 operators influence the mono-Higgs signal and are relevant for dark matter searches.

Abstract

We investigate the potential of the channel {\em mono-Higgs + MET} in yielding signals of dark mater at the high-luminosity Large Hadron Collider (LHC). As illustration, a scalar dark matter in a Higgs portal scenario has been chosen, whose phenomenological viability has been ensured by postulating the existence of dimension-6 operators that enable cancellation in certain amplitudes for elastic scattering of dark matter in direct search experiments. These operators are found to have non-negligible contribution to the mono-Higgs signal. Thereafter, we carry out a detailed analysis of this signal, with the accompanying MET providing a useful handle in suppressing backgrounds. Signals for the Higgs decaying into both the diphoton and $b{\bar b}$ channels have been studied. A cut-based simulation is presented first, followed by a demonstration of how the statistical significance can be improved through analyses based on Boosted Decision Trees and Artificial Neural Network. The improvement is found to be especially noticeable for the $b{\bar b}$ channel.