JUNO Sensitivity to Invisible Decay Modes of Neutrons

TL;DR

This paper investigates JUNO's potential to detect neutron invisible decay modes by analyzing correlated signals from residual nuclei, estimating backgrounds, and projecting sensitivities over ten years, aiming to improve current limits significantly.

Contribution

It introduces a novel method to search for neutron invisible decays in JUNO using triple coincidence signals and advanced background suppression techniques.

Findings

Projected sensitivity for neutron decay lifetime exceeds current limits by an order of magnitude.

Utilizes Monte Carlo simulations with latest data for background estimation.

Employs pulse shape discrimination and multivariate analysis for background reduction.

Abstract

We explore the decay of bound neutrons into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector, which do not produce an observable signal. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$.