Optimal signal discrimination in a Low signal-to-noise ratio environment

Energy measurements from calorimeter information are very important for particle detection in high-energy physics experiments. Calorimeters have a very good energy resolution, but some interesting particles produce a signal rather close to electronic noise values. This work presents the development of optimal signal discriminators to be implemented in a low signal- to-noise environment. They use signals from a highly segmented calorimeter (TileCal), which was built in the context of the ATLAS experiment for the Large Hadron Collider, operating at the European Organization for Nuclear Research (CERN).