A Feature-Extraction And Pile-Up Reconstruction Algorithm For The Forward-Spectrometer Emc Of The Panda Experiment

A digital algorithm for real-time feature extraction, i.e. determination of pulse amplitude and timing, has been developed for the forward-spectrometer electromagnetic calorimeter in the PANDA experiment. The algorithm, which is based on the well known optimal-filter algorithm, has been designed to allow reconstruction of pile-up signals in real time and to work in a free-running DAQ system such as PANDA. To benchmark the algorithm, a Geant4-based Monte Carlo model of photon interactions in the calorimeter has been developed to generate realistic detector signals which were used as inputs to a VHDL simulation of the algorithm. The results of this simulation study show that the developed algorithm improves the time resolution by almost 50% compared to a conventional linear constant fraction discriminator algorithm. For the PANDA calorimeter, this results in a time root resolution close to 100 ps/ GeV per detector element at high energies. The algorithm allows reconstruction of the amplitude and timing of pile-up pulses separated by as little as 30 ns with good efficiency, fulfilling the PANDA requirements.