The Fast Stochastic Matching Pursuit for Neutrino and Dark Matter Experiments

Abstract

Photomultiplier tubes (PMTs) are widely deployed at neutrino and dark matter experiments for photon counting. When multiple photons hit a PMT consecutively, their photo-electron (PE) pulses pile up to hinder the precise measurements of the count and timings. We introduce Fast Stochastic Matching Pursuit (FSMP) to analyze the PMT signal waveforms into individual PEs with the strategy of reversible-jump Markov-chain Monte Carlo. We demonstrate that FSMP improves the energy and time resolution of PMT-based experiments and gains acceleration on GPUs. It is suitable for dynode PMTs, and is extensible to microchannel-plate (MCP) PMTs. In the condition of our laboratory characterization of 8-inch MCP-PMTs, FSMP improves the energy resolution by up to 10% from the conventional method of waveform integration.