Search for Single Top Quark Production at the D0 Experiment using Bayesian Neural Networks

Abstract

We present the methodology used to measure the single top quark production cross section in the D0 experiment, and show as an example the results that led to the first evidence of single top quark production in D0 at the Fermilab Tevatron proton-antiproton collider. The selected events are mostly backgrounds, which we separate from the expected signals using three multivariate analysis techniques, one of them being Bayesian neural networks, which we will describe here.