electronics Article Muon–Electron Pulse Shape Discrimination for Water Cherenkov Detectors Based on FPGA/SoC Luis Guillermo Garcia 1,2,*,† , Romina Soledad Molina 1,2,3,*,† , Maria Liz Crespo 1 , Sergio Carrato 2, Giovanni Ramponi 2 , Andres Cicuttin 1, Ivan Rene Morales 4 and Hector Perez 4 1 MLAB, The Abdus Salam International Centre for Theoretical Physics (ICTP), 34151 Trieste, Italy;
[email protected] (M.L.C.);
[email protected] (A.C.) 2 DIA, Università degli Studi di Trieste (UNITS), 34127 Trieste, Italy;
[email protected] (S.C.);
[email protected] (G.R.) 3 LEIS, Universidad Nacional de San Luis (UNSL), San Luis D5700HHW, Argentina 4 ECFM, Universidad de San Carlos de Guatemala (USAC), Guatemala 01012, Guatemala;
[email protected] (I.R.M.);
[email protected] (H.P.) * Correspondence:
[email protected] (L.G.G.);
[email protected] (R.S.M.) † These authors contributed equally to this work. Abstract: The distinction of secondary particles in extensive air showers, specifically muons and electrons, is one of the requirements to perform a good measurement of the composition of primary cosmic rays. We describe two methods for pulse shape detection and discrimination of muons and electrons implemented on FPGA. One uses an artificial neural network (ANN) algorithm; the other exploits a correlation approach based on finite impulse response (FIR) filters. The novel hls4ml package is used to build the ANN inference model. Both methods were implemented and tested on Xilinx FPGA System on Chip (SoC) devices: ZU9EG Zynq UltraScale+ and ZC7Z020 Zynq. The data set used for the analysis was captured with a data acquisition system on an experimental site based on a water Cherenkov detector.