Usage of Neural Networks for Separating Anomalous Left and Right Vector Wtb Couplings in the Processes of tWb Associated Sngle Top Quark Production

Abstract

The paper presents initial steps to distinguish the contribution of anomalous operators in Wtb vertex from the Standard Model for final state processes tWb using a deep neural network. A scenario with vector left- and right-handed operators at the Wtb vertex is considered as an example and as a most difficult for the separation. The deep neural network was trained on preselected kinematic variables that exhibit different behavior for the Standard Model cases and the presence of a right vector operator at the Wtb vertex. The presented results can be interpreted in the context of further prospects for searching for anomalous operators in Wtb vertex for the processes of single- and double-resonant production of top quarks with the final state tWb.