Search for flavor-changing neutral currents via anomalous ctH and utH couplings

In this master thesis, flavour-changing neutral currents are investigated at a center- of-mass energy of $\sqrt{s} = 13\;$TeV with the ATLAS detector. Two different flavor-changing neutral current processes are investigated. These processes arise either from an anomalous $ctH$ or $utH$ coupling. The search for them is complicated due to the large amount of background events from processes like $t\bar{t}$ and single top-quark production. In order to optimize the search for the flavour-changing neutral current processes, neural networks are used to construct a discriminant, which strongly separates signal events from background events. To train the neural network, kinematic properties of the signal and background processes are used. The main part of this thesis focuses on the optimization of the neural networks. The optimized neural networks are used to determine an expected upper exclusion limit on the branching ratios of the flavour-changing neutral current processes. For this, a binned profile likelihood fit is performed with the help of a statistical evaluation framework, including statistical and systematic uncertainties. The expected upper exclusion limit on the branching ratio for the left-handed processes are: $\mathcal{B}\,(t\rightarrow uH)=1.59×10^{−3}$ and $\mathcal{B}\,(t\rightarrow cH)=3.33×10^{−3}$.