Mass Hierarchy Determination Using Neutrinos from Multiple Reactors

TL;DR

This study uses Monte Carlo simulations to evaluate how the placement of detectors relative to multiple reactors affects the ability to determine the neutrino mass hierarchy, proposing optimal locations and analysis methods.

Contribution

It introduces a method for optimizing detector placement and analysis techniques to improve neutrino mass hierarchy determination in reactor experiments.

Findings

Perpendicular detector placement improves hierarchy sensitivity.

Optimal detector location is beneath a 1000m mountain 44.5 km from reactors.

Neural network analysis slightly outperforms traditional methods.

Abstract

We report the results of Monte Carlo simulations of a medium baseline reactor neutrino experiment. The difference in baselines resulting from the 1 km separations of Daya Bay and Ling Ao reactors reduces the amplitudes of 1-3 oscillations at low energies, decreasing the sensitivity to the neutrino mass hierarchy. A perpendicular detector location eliminates this effect. We simulate experiments under several mountains perpendicular to the Daya Bay/Ling Ao reactors, considering in particular the background from the TaiShan and YangJiang reactor complexes. In general the hierarchy can be determined most reliably underneath the 1000 meter mountain BaiYunZhang, which is 44.5 km from Daya Bay. If some planned reactors are not built then nearby 700 meter mountains at 47-51 km baselines gain a small advantage. Neglecting their low overhead burdens, hills near DongKeng would be the optimal locations. We use a weighted Fourier transform to avoid a spurious dependence on the high energy neutrino spectrum and find that a neural network can extract quantities which determine the hierarchy marginally better than the traditional RL + PV.