Low Energy Event Reconstruction in IceCube DeepCore

TL;DR

This paper introduces two advanced algorithms for reconstructing low-energy neutrino events in IceCube DeepCore, improving directional and energy resolution crucial for physics analyses.

Contribution

It presents novel algorithms tailored for low-energy event reconstruction in IceCube DeepCore, addressing challenges not covered by existing high-energy methods.

Findings

Fast directional reconstruction based on unscattered light.

Likelihood-based reconstruction with superior resolution.

Algorithms enable better analysis of low-energy neutrino events.

Abstract

The reconstruction of event-level information, such as the direction or energy of a neutrino interacting in IceCube DeepCore, is a crucial ingredient to many physics analyses. Algorithms to extract this high level information from the detector's raw data have been successfully developed and used for high energy events. In this work, we address unique challenges associated with the reconstruction of lower energy events in the range of a few to hundreds of GeV and present two separate, state-of-the-art algorithms. One algorithm focuses on the fast directional reconstruction of events based on unscattered light. The second algorithm is a likelihood-based multipurpose reconstruction offering superior resolutions, at the expense of larger computational cost.