Real-Time Wiener Deconvolution algorithm on FPGA for neutrino physics

Abstract This work presents an advanced Real-Time Wiener Deconvolution algorithm designed to take advantage of the FPGAs integrated into the JUNO experiment large PMT readout electronics. Exploiting online reconstruction of the signal generated by PMTs, we expect to enable the detection of low energy depositions, like those generated by transient astrophysical phenomena. The features of the algorithm are presented, including its capacity to manage high-throughput data streams with minimal latency, its adaptability and resilience in discerning the characteristics of the input data. The performance of the algorithm are evaluated and compared with the currently used solution, Continuous Over-Threshold integration, showing an improvement in photoelectrons detection for pile-up conditions that reaches offline performances and a better charge reconstruction, comparable with more complex algorithms. These results show the potential of FPGA-based solutions for real-time waveform reconstruction in neutrino experiments.