An overview of the BaBar detector, the physics goals and the current state of the project will be given. After the general introduction to Artificial Neural Networks, including interesting physics and 'real life' examples of their applications, the focus of the talk will shift towards the studies I completed so far. In order to compare the Artificial Neural Network approach to HEP analysis against the traditional methods a toy model consisting of two types of particles defined by four generic properties was designed. A number of `events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed.

Thursday, November 19th 1998, 15:30
Ernest Rutherford Physics Building, room 305