Seafloor Topography Enhances KM3NeT Sensitivity to ANITA-like Events

TL;DR

This paper shows that local underwater topography around KM3NeT enhances its sensitivity to ultra-high-energy neutrino events, especially for long-lived particles, and proposes a model explaining recent anomalous detections while reducing tensions with other experiments.

Contribution

It introduces the concept of topographic enhancement for neutrino detection and provides a model that explains recent events, reducing tension with IceCube data.

Findings

Topography can increase detection efficiency by up to a factor of 3.

A simplified model explains KM3NeT and ANITA-IV observations simultaneously.

Including azimuthal information constrains the parameter space more effectively.

Abstract

In this article, we introduce the concept of \textit{topographic enhancement} in the context of ultra-high-energy neutrino detection by underwater neutrino telescopes. We demonstrate that the local topography around KM3NeT/ARCA can increase the detection efficiency in scenarios involving long-lived particles by up to a factor of $\sim 3$ due to the presence of an underwater mountain range in the direction of Malta. We consider a simplified model-independent approach that parametrizes the new physics able to generate both track-like and cascade-like signals in neutrino telescopes. When explaining the KM3-230213A event with a diffuse dark flux hypothesis, including its azimuthal direction--in addition to the zenith angle--provides additional constraints on the parameter space. In this effective model, the observations by KM3NeT and ANITA-IV can be simultaneously explained and the global tension with the lack of a corresponding detection in IceCube is reduced to 2.4 sigma. This work underscores the importance of incorporating topographic effects in the design and optimization of next-generation neutrino telescopes, as is done in the context of mountain-based detectors such as TAMBO. We present a numerical code which can be used to easily extend this topographical analysis to other experiments.