Sub-GeV Dark Matter Detection with Dark Rates in Liquid Scintillators
Lillian Santos-Olmsted, Rebecca K. Leane, Carlos Blanco, John F. Beacom
TL;DR
This work tackles the challenge of probing sub-GeV dark matter by repurposing large liquid-scintillator neutrino detectors to search for DM-induced light via two channels: excitation and ionization. By generalizing prior excitation-only analyses to include ionization and by extending the study to JUNO, SNO+, Daya Bay, Borexino, and KamLAND, the authors provide a comprehensive framework for DM-electron scattering searches using annual modulation of the PMT hit rate. Their approach combines benzene-based excitation form factors, atomic ionization form factors, detector light yield, and efficiency to compute signal rates and 95% CL sensitivities across multiple detectors and mediator scenarios (heavy and light). The results show that JUNO and Borexino can outperform some direct-detection constraints for MeV-scale DM, especially under a heavy mediator, while a light mediator yields strong sensitivity from excitation across the whole mass range; crucially, a coordinated multi-detector program offers cross-checks and robustness, leveraging differing systematics and detector properties. Overall, this work demonstrates a practical path to robust sub-GeV DM constraints using existing and near-future liquid-scintillator experiments, with significant potential for early data-driven validation and cross-experiment discovery potential.
Abstract
It was recently shown that standard sub-GeV dark matter candidates can be effectively probed by large neutrino observatories via annual modulation of the total photomultiplier hit rate. That work focused on the production of light by the excitation of scintillator molecules and considered the JUNO detector, surpassing limits from dedicated dark-matter detectors and reaching theoretical targets. Here, we significantly generalize that work, now also taking into account ionization channels and extending the analysis to other liquid-scintillator detectors, including SNO+, Daya Bay, Borexino, and KamLAND. Last, we present a call to action: with multiple detectors achieving competitive sensitivity, there is an opportunity to validate this new technique across experiments and to refine it using each detector's strengths.
