A New Approach to Background Subtraction in Low-Energy Neutrino Experiments

TL;DR

This paper introduces a novel background subtraction method for low-energy neutrino experiments that leverages background symmetry to improve signal extraction and reduce measurement errors.

Contribution

The paper presents a new background cancellation technique based on symmetry, significantly enhancing data accuracy in neutrino detection experiments.

Findings

Reduced measurement errors from ~20% to ~10% in the Palo Verde experiment.

Applicable to future experiments like KamLAND and LENS for improved data quality.

Demonstrated effectiveness of symmetry-based background subtraction.

Abstract

We discuss a new method to extract neutrino signals in low energy experiments. In this scheme the symmetric nature of most backgrounds allows for direct cancellation from data. The application of this technique to the Palo Verde reactor neutrino oscillation experiment allowed us to reduce the measurement errors on the anti-neutrino flux from $\sim 20$% to $\sim 10$%. We expect this method to substantially improve the data quality in future low background experiments such as KamLAND and LENS.