Neural Networks for Analysis of Top Quark Production

Abstract

Neural networks (NNs) provide a powerful and flexible tool for selecting a signal from a larger background. The D0 collaboration has used them extensively in studying t-tbar decays. NNs were essential to the measurement of the t-tbar production cross section in the all-jets channel (t tbar -> b bbar qqqq, and were also used in the measurement of the mass of the top quark in the lepton+jets channel (t tbar -> b bbar l nu q qbar). This paper will describe two new applications of neural networks to top~quark analysis: the search for single top~quark production, and an effort to increase the sensitivity in the dilepton channel t tbar -> b bbar e mu nu nu beyond that achieved in the published analysis.