An online calorimeter trigger for removing outsiders from particle beam calibration tests

An online neural triggering system for particle identification is presented. It is developed for calibration tests with Tilecal, the hadronic calorimeter of the ATLAS experiment. The proposed neural system proves to cope with the required data input rate and achieves more than 99.7% in particle classification efficiency, even when significant particle contamination is observed in the data samples.