Searches for the rare tWZ and tWγ processes at the LHC using machine learning techniques

This thesis work presents the first searches and the first evidences for the \(tWZ \) and \(tW\gamma\) processes at the LHC with the CMS experiment. The analyses employ proton-proton collision data corresponding to an integrated luminosity of 138 fb\(^{-1}\) collected during Run 2 of the LHC between 2016 and 2018.

Purpose-built Machine Learning algorithms are developed in these searches in order to discriminate the rare signal processes from the large background, consisting mostly of production processes of top quark pairs in association with a \(Z\) boson or a photon.

Additionally, this thesis describes the treatments used to describe the modeling and simulation of the \(tWZ \) and \(tW\gamma\) production process.