Novel event classification based on spectral analysis of scintillation waveforms in Double Chooz

TL;DR

This paper introduces a novel spectral analysis method for scintillation waveforms that significantly improves event classification and background rejection in neutrino detectors, demonstrated in the Double Chooz experiment.

Contribution

The paper presents a new Fourier spectral analysis technique for pulse shape discrimination that enhances event classification performance in large liquid scintillator detectors.

Findings

Effective differentiation between detector volumes.

High rejection efficiency of instrumental noise.

Sensitivity to particle types like muons and alpha particles.

Abstract

Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in large detectors. This paper describes a novel approach for a pulse shape based event classification developed in the context of the Double Chooz reactor antineutrino experiment. Unlike previous implementations, this method uses the Fourier power spectra of the scintillation pulse shapes to obtain event-wise information. A classification variable built from spectral information was able to achieve an unprecedented performance, despite the lack of optimization at the detector design level. Several examples of event classification are provided, ranging from differentiation between the detector volumes and an efficient rejection of instrumental light noise, to some sensitivity to the particle type, such as stopping muons, ortho-positronium formation, alpha particles as well as electrons and positrons. In combination with other techniques the method is expected to allow for a versatile and more efficient background rejection in the future, especially if detector optimization is taken into account at the design level.