Time-Structured Tail Probabilities for Ultra-High-Energy Gamma-Hadron Discrimination in Water-Cherenkov Arrays

TL;DR

This paper introduces a new time-structured tail probability variable for water-Cherenkov detectors, significantly improving gamma-hadron discrimination at ultra-high energies by leveraging the time structure of signals.

Contribution

The paper presents a novel discrimination variable, $P^{ ext{α, T}}_{ ext{tail}}$, that incorporates time-resolved signal information, enhancing ultra-high-energy gamma-ray detection capabilities.

Findings

Achieves roughly 2% background contamination at 50% gamma efficiency.

Improves discrimination performance by nearly a factor of five over existing methods.

Approaches the performance of an ideal muon-isolating detector.

Abstract

Gamma-hadron discrimination based on shower observables is essential for identifying gamma-ray astrophysical sources at the highest energies. In this work, we introduce $P^{\alpha, T}_{\rm tail}$, a new discrimination variable for ultra-high-energy photon searches within the framework of a water-Cherenkov detector (WCD) array. The observable extends signal-integrated methods by incorporating the time structure of WCD traces, using cumulative signal distributions. Using simulated proton- and gamma-induced air showers at energies around $10^{17}\,\mathrm{eV}$, we evaluate the performance of $P^{\alpha, T}_{\rm tail}$ and compare it with established WCD-based observables such as $S_b$, risetime-based variables, and the SWGO-inspired, $P^\alpha_{\rm tail}$. The new variable attains a background contamination of roughly $2 \times 10^{-2}$ at $50\%$ gamma efficiency, improving upon existing WCD-only methods by nearly a factor of five and approaching the performance of an idealized muon-isolating reference. These results demonstrate the effectiveness of exploiting time-resolved signal tails to enhance ultra-high-energy photon searches in sparse surface arrays.