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Open AccessArticle

Muon–Electron Pulse Shape Discrimination for Water Cherenkov Detectors Based on FPGA/SoC

1
MLAB, The Abdus Salam International Centre for Theoretical Physics (ICTP), 34151 Trieste, Italy
2
DIA, Università degli Studi di Trieste (UNITS), 34127 Trieste, Italy
3
LEIS, Universidad Nacional de San Luis (UNSL), San Luis D5700HHW, Argentina
4
ECFM, Universidad de San Carlos de Guatemala (USAC), Guatemala 01012, Guatemala
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: John Ball
Electronics 2021, 10(3), 224; https://doi.org/10.3390/electronics10030224
Received: 31 December 2020 / Revised: 12 January 2021 / Accepted: 15 January 2021 / Published: 20 January 2021
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. A comparison of the accuracy of the detection, resources utilization and power consumption of both methods is presented. The results show an overall accuracy on particle discrimination of 96.62% for the ANN and 92.50% for the FIR-based correlation, with execution times of 848 ns and 752 ns, respectively. View Full-Text
Keywords: FPGA; neural network; FIR; pulse shape discrimination; WCD; muon; electron FPGA; neural network; FIR; pulse shape discrimination; WCD; muon; electron
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MDPI and ACS Style

Garcia, L.G.; Molina, R.S.; Crespo, M.L.; Carrato, S.; Ramponi, G.; Cicuttin, A.; Morales, I.R.; Perez, H. Muon–Electron Pulse Shape Discrimination for Water Cherenkov Detectors Based on FPGA/SoC. Electronics 2021, 10, 224. https://doi.org/10.3390/electronics10030224

AMA Style

Garcia LG, Molina RS, Crespo ML, Carrato S, Ramponi G, Cicuttin A, Morales IR, Perez H. Muon–Electron Pulse Shape Discrimination for Water Cherenkov Detectors Based on FPGA/SoC. Electronics. 2021; 10(3):224. https://doi.org/10.3390/electronics10030224

Chicago/Turabian Style

Garcia, Luis G.; Molina, Romina S.; Crespo, Maria L.; Carrato, Sergio; Ramponi, Giovanni; Cicuttin, Andres; Morales, Ivan R.; Perez, Hector. 2021. "Muon–Electron Pulse Shape Discrimination for Water Cherenkov Detectors Based on FPGA/SoC" Electronics 10, no. 3: 224. https://doi.org/10.3390/electronics10030224

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