Charge reconstruction in large-area photomultipliers

TL;DR

This paper introduces a novel signal processing method using Wiener filtering and Fourier deconvolution to accurately reconstruct PMT charge in high pile-up scenarios, achieving near-perfect accuracy up to 15 PEs.

Contribution

It presents an experimental charge reconstruction technique for large PE pile-up in PMTs, combining Wiener filtering and Fourier deconvolution for unbiased results.

Findings

Achieves charge reconstruction unbiased at the permille level up to 15 PEs.

Significantly improves linear regression slope from 0.769 to 0.989 with deconvolution.

Provides an open-source C++ implementation of the algorithm.

Abstract

Large-area PhotoMultiplier Tubes (PMT) allow to efficiently instrument Liquid Scintillator (LS) neutrino detectors, where large target masses are pivotal to compensate for neutrinos' extremely elusive nature. Depending on the detector light yield, several scintillation photons stemming from the same neutrino interaction are likely to hit a single PMT in a few tens/hundreds of nanoseconds, resulting in several photoelectrons (PEs) to pile-up at the PMT anode. In such scenario, the signal generated by each PE is entangled to the others, and an accurate PMT charge reconstruction becomes challenging. This manuscript describes an experimental method able to address the PMT charge reconstruction in the case of large PE pile-up, providing an unbiased charge estimator at the permille level up to 15 detected PEs. The method is based on a signal filtering technique (Wiener filter) which suppresses the noise due to both PMT and readout electronics, and on a Fourier-based deconvolution able to minimize the influence of signal distortions ---such as an overshoot. The analysis of simulated PMT waveforms shows that the slope of a linear regression modeling the relation between reconstructed and true charge values improves from $0.769 \pm 0.001$ (without deconvolution) to $0.989 \pm 0.001$ (with deconvolution), where unitary slope implies perfect reconstruction. A C++ implementation of the charge reconstruction algorithm is available online at http://www.fe.infn.it/CRA .