Application of Machine Learning for the Analysis of Higgs Boson Production in Association with Single Top-Quark

Abstract

This work describes results of application of a neural network for the classification of the Higgs boson in association with a single top quark signal production \(pp \to tH\) and the main background processes \(pp \to tt,ttH,ttW,ttZ\) production at the LHC in the ATLAS experiment. The tH channel is sensitive to the sign of the tH-coupling unlike the ttH. Also, an accurate measurement of the Higgs-top coupling is sensitive to the Beyond the Standard Model physics [1, 2].