WavePID: Studies of DOM-level waveform timing for track vs. cascade discrimination in IceCube at 5-100 GeV

TL;DR

This paper introduces WavePID, a waveform-based likelihood discriminator for improved track versus cascade classification in IceCube's low-energy neutrino data, enhancing purity and robustness in sparse hit scenarios.

Contribution

WavePID is a novel, physics-motivated likelihood method that leverages waveform timing for better particle identification in low-energy IceCube data.

Findings

Cascade purity improved by ~5 percentage points at 20% down-selection.

WavePID maintains Data-MC agreement within systematics.

Method is robust with sparse observations.

Abstract

The IceCube Neutrino Observatory is a cubic-kilometer Cherenkov detector embedded in the Antarctic ice at the South Pole. Its densely instrumented sub-array and dedicated low-energy analyses provide sensitivity to neutrinos in the 5-100 GeV range, enabling precision studies of neutrino oscillations and searches for new physics. This work focuses specifically on this low-energy regime, where sparse hit patterns limit the performance of topology-based reconstruction and classification methods. We introduce Waveform-based Particle Identification (WavePID), a statistically rigorous and interpretable likelihood-ratio discriminator for track-cascade separation, built from Monte Carlo templates in timing-aware, physics-motivated observables and validated through dedicated simulations. Applied to both Monte Carlo and 11.1 years of IceCube data, WavePID suggests improved cascade purity by about 5 percentage points at a fixed 20% down-selection rate relative to the current leading cascade selection, while maintaining Data-MC agreement within detector systematics. The approach is compact and robust to sparse observations, demonstrating the value of waveform-level timing for low-energy reconstruction.