Signal identification with Kalman Filter towards background-free neutrinoless double beta decay searches in gaseous detectors

TL;DR

This paper introduces a Bayesian Kalman Filter method for reconstructing electron tracks in gaseous detectors, significantly improving background suppression and enhancing the sensitivity of neutrinoless double beta decay searches.

Contribution

A novel Kalman Filter-based approach for track reconstruction in gaseous detectors, enabling better background discrimination in $0 u eta eta$ searches.

Findings

Background can be suppressed by an order of magnitude.

The method approaches background-free detection regime.

Sensitivity of the PandaX-III experiment is significantly improved.

Abstract

Particle tracks and differential energy loss measured in high pressure gaseous detectors can be exploited for event identification in neutrinoless double beta decay~($0\nu \beta \beta$) searches. We develop a new method based on Kalman Filter in a Bayesian formalism (KFB) to reconstruct meandering tracks of MeV-scale electrons. With simulation data, we compare the signal and background discrimination power of the KFB method assuming different detector granularities and energy resolutions. Typical background from $^{232}$Th and $^{238}$U decay chains can be suppressed by another order of magnitude than that in published literatures, approaching the background-free regime. For the proposed PandaX-III experiment, the $0\nu \beta \beta$ search half-life sensitivity at the 90\% confidence level would reach $2.7 \times 10^{26}$~yr with 5-year live time, a factor of 2.7 improvement over the initial design target.