Machine learning techniques for pile-up rejection in cryogenic calorimeters: development and characterization
Anno
2021
Proponente Guido Fantini - Ricercatore
Struttura
Sottosettore ERC del proponente del progetto
PE2_2
Componenti gruppo di ricerca
| Componente | Categoria |
|---|---|
| Fabio Bellini | Aggiungi Tutor di riferimento (Professore o Ricercatore afferente allo stesso Dipartimento del Proponente) |
Abstract
CUPID (CUORE Upgrade with Particle IDentification) is a foreseen tonne-scale array of (LMO) cryogenic calorimeters with double readout of heat and light signals. One of the dominant background sources is pile-up of standard-model double beta decay events in the same crystal detector.
It is crucial to achieve a time difference pile-up rejection of ~ 300 us while keeping a high efficiency for single decay events.
The goal of this project is to develop machine learning techniques to perform event classification with supervised learning of heater generated pile-up events.
ERC
PE1_18, PE2_2
Keywords:
INTELLIGENZA ARTIFICIALE, FISICA DEI NEUTRINI, ELABORAZIONE DEI SEGNALI