# Background Discrimination for Neutrinoless Double Beta Decay in Liquid Xenon Using Cherenkov Light

## TL;DR

This paper explores using Cherenkov light detection in liquid xenon to distinguish neutrinoless double beta decay events from background noise, aiming to improve experimental sensitivity.

## Contribution

It introduces a simulation-based method combining Cherenkov light analysis with machine learning to classify decay events in liquid xenon detectors.

## Key findings

- Cherenkov light provides some discrimination between signal and background.
- The technique offers modest sensitivity improvements.
- Limitations arise from decay kinematics and electron scattering.

## Abstract

Neutrinoless double beta decays in liquid xenon produce a significant amount of Cherenkov light, with a photon number and angular distribution that distinguishes these events from common backgrounds. A GEANT4 simulation was used to simulate Cherenkov photon production and measurement in a liquid xenon detector and a multilayer perceptron was used to analyze the resulting distributions to classify events based on their Cherenkov photons. Our results show that a modest improvement in the sensitivity of neutrinoless double beta decay searches is possible using this technique, but the kinematics of the neutrinoless double beta decay and electron scattering in liquid xenon substantially limit this approach.