Machine Learning Techniques for Pile-Up Rejection in Cryogenic Calorimeters

CUORE Upgrade with Particle IDentification (CUPID) is a foreseen ton-scale array of Li2MoO4 (LMO) cryogenic calorimeters with double readout of heat and light signals. Its scientific goal is to fully explore the inverted hierarchy of neutrino masses in the search for neutrinoless double beta decay of Mo-100. Pile-up of standard double beta decay of the candidate isotope is a relevant background. We generate pile-up heat events via injection of Joule heater pulses with a programmable waveform generator in a small array of LMO crystals operated underground in the Laboratori Nazionali del Gran Sasso, Italy. This allows to label pile-up pulses and control both time difference and underlying amplitudes of individual heat pulses in the data. We present the performance of supervised learning classifiers on data and the attained pile-up rejection efficiency.

Automated summary

CUORE Upgrade with Particle IDentification (CUPID) is a planned large-scale experiment that aims to explore the inverted hierarchy of neutrino masses and search for neutrinoless double beta decay of Mo-100 by studying the heat and light signals of a Li2MoO4 (LMO) cryogenic calorimeter array. Pile-up events from standard double beta decay of the candidate isotope are considered as relevant background, and the experiment involves injecting Joule heater pulses to generate pile-up heat events in a small array of LMO crystals operated underground. The performance of supervised learning classifiers on the data and the achieved pile-up rejection efficiency are presented.