Charge reconstruction in large-area photomultipliers

The International School for Advanced Studies (SISSA), find out more The International School for Advanced Studies (SISSA), find out more Charge reconstruction in large-area photomultipliers M. Grassi1,2, M. Montuschi3,4, M. Baldoncini3,4, F. Mantovani3,4, B. Ricci3,4, G. Andronico5, V. Antonelli1,11, M. Bellato7, E. Bernieri8,9, A. Brigatti1,11Show full author list Published 6 February 2018 • © 2018 IOP Publishing Ltd and Sissa Medialab Journal of Instrumentation, Volume 13, February 2018 Citation M. Grassi et al 2018 JINST 13 P02008 Download Article PDF References 95 Total downloads 2 2 total citations on Dimensions. Article has an altmetric score of 1 Turn on MathJax Get permission to re-use this article Share this article Share this content via email Share on Facebook (opens new window) Share on Twitter (opens new window) Share on Mendeley (opens new window) Article information 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 ± 0.001 (without deconvolution) to 0.989 ± 0.001 (with deconvolution), where unitary slope implies perfect reconstruction. A C++ implementation of the charge reconstruction algorithm is available online at [1].