# Constraint on the solar $\Delta m^2$ using 4,000 days of short baseline reactor neutrino data

## TL;DR

This paper uses 4,000 days of short baseline reactor neutrino data from Daya Bay and RENO to constrain the solar $ m^2$, providing an upper limit that complements existing measurements and will improve with more data.

## Contribution

It introduces a method to constrain solar  m^2 using publicly available short baseline reactor neutrino data, achieving a new upper limit and demonstrating potential for future improvements.

## Key findings

- Combined Daya Bay and RENO data set an upper limit of 18  10^{-5} eV^2 on solar  m^2 at 95% C.L.
- The constraint is slightly more than twice the KamLAND value.
- Results are statistically limited but will improve with additional data.

## Abstract

There is a well known 2$\sigma$ tension in the measurements of the solar $\Delta m^2$ between KamLAND and SNO/Super-KamioKANDE. Precise determination of the solar $\Delta m^2$ is especially important in connection with current and future long baseline CP violation measurements. Reference \cite{Seo:2018rrb} points out that currently running short baseline reactor neutrino experiments, Daya Bay and RENO, can also constrain solar $\Delta m^2$ value as demonstrated by a GLoBES simulation with a limited systematic uncertainty consideration. In this work, the publicly available data, from Daya Bay (1,958 days) and RENO (2,200 days) are used to constrain the solar $\Delta m^2$. Verification of our method through $\Delta m^2_{ee}$ and $\sin^2 \theta_{13}$ measurements is discussed in Appendix A. Using this verified method, reasonable constraints on the solar $\Delta m^2$ are obtained using above Daya Bay and RENO data, both individually and combined. We find that the combined data of Daya Bay and RENO set an upper limit on the solar $\Delta m^2$ of 18 $\times 10^{-5}$ eV$^2$ at the 95% C.L., including both systematic and statistical uncertainties. This constraint is slightly more than twice the KamLAND value. As this combined result is still statistics limited, even though driven by Daya Bay data, the constraint will improve with the additional running of this experiment.