| We have analyzed the 90 pb-1 of data from Run1B at CDF in order to extract the top/anti-top quark (tt¯) production cross section. This analysis uses a set of kinematic variables to discriminate the tt¯ signal from the W-boson + jets(W + jets) background. Unlike CDF's previous top cross section measurements, tagging of b quarks is not required here. Using a Artificial Neural Network (ANN) the kinematic variables were combined into a single discrimination parameter. With this parameter we performed a binned maximum likelihood fit of our data sample to Monte Carlo generated background (W + jets) and signal (tt¯) distributions. Taking the minimum of the negative log-likelihood value, we determine the most probable number of signal events in our sample, do a background subtraction and use this number (N tt¯) to extract the tt¯ cross section, with a resulting total tt¯ cross section of sigma tt¯ = 5.1+1.5-1.6 pb. |
