• single top cdf wham neural network acceptance

We present the Single Top in W+jets analysis at CDF II using 7.5 fb−1 of p¯p data. We select events in the W + jets topology consistent with the signature of a charged lepton (electron or muon), large missing transverse energy (MET) from the W boson decay and two or three jets, at least one of them is required to be identified as originating from a b quark. We use the new POWHEG Monte Carlo generator for single top signal samples in s-channel, t-channel and Wt-channel, which are generated at NLO accuracy, with an assumed top quark mass of 172.5 GeV/c^2. The Neural Network multivariate method is used to discriminate signal against comparatively large backgrounds.
The thesis work was mostly focused on event selection and background estimation part of the analysis: we improved the signal acceptance by about 20%, by including more lepton categories and also reduced some backgrounds with dedicated selection.
At the end we present the final cross section results, which are the new CDF II measurement for Single Top events.