NEURAL NETWORK TECHNIQUES FOR A RUN II SEARCH 0F SINGLE TOP PRODUCTION AT CDF

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Abstract
At the Tevatron Collider it is possible to create single top quarks in the final state via either off mass shell W production (W*), or the W-gluon fusion process. The Standard Model predicts a production cross section of only a few picobarns. In addition, the backgrounds for single top production at large. The datasets collected during Run I at the Tevatron were not sufficiently large to extract the signal from the large W+jets background. In Run II at the Tevatron, we expect to collect 2 fb -1 of data, a twenty fold increase. We present here a method of searching for single top production using the Artificial Neural Network technique. We will describe the technique and present results based on Monte Carlo studies. We will demonstrate that the Neural Net approach is well suited for extracting the signal from a sample with a poor signal-to-background ratio.

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