Implementation of a kinematic fit of single top-quark production in association with a W boson and its implementation in a neural-network-based analysis in ATLAS

In order to provide discrimination between the $Wt$ channel signal and its backgrounds for analyses that try to measure single top-quark production in the $Wt$ channel, a kinematic fit to the lepton+jets decay mode of the $Wt$ channel has been implemented using the KLFitter package. The fit has been validated by studying its performance in terms of the efficiency of the fit to correctly assign the final-state quarks of the fit model to the measured jets as a function of various parameters, as well as the improvement of the energy resolutions of the fitted particles due to the fit. By combining the output variables of the kinematic fitter using neural networks, it has been shown that the fit results are suitable to identify the decay mode of the top quark in $Wt$ events and to identify whether the kinematic fit succeeded in correctly assigning the final-state quarks to the measured jets. In order to demonstrate the value of the kinematic fit for analysis, another neural network - again using strictly results of the kinematic fit as input - has been trained to separate to the $Wt$ channel signal from its backgrounds. A separation power comparable to a conventional neural-network-based $Wt$ channel analysis has been achieved.