Low Energy Event Reconstruction in IceCube DeepCore

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.

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Cited by in corpus (7)

• Measurement of Atmospheric Neutrino Mixing with Improved IceCube DeepCore Calibration and Data Processing
• Graph Neural Networks for Low-Energy Event Classification & Reconstruction in IceCube
• Search for sub-TeV Neutrino Emission from Novae with IceCube-DeepCore
• Search for GeV-scale Dark Matter from the Galactic Center with IceCube-DeepCore
• Resolution Limiting Factors in Low-Energy Cascade Zenith Angle Reconstruction with the IceCube Upgrade
• Measurement of the inelasticity distribution of neutrino-nucleon interactions for $80\mathbf{GeV}<{\mathbf{E}}_{\nu }<560\mathbf{GeV}$ with IceCube DeepCore
• ${\delta }_{CP}$-free constraints on NSI parameters ${\epsilon }_{e\mu }$ and ${\epsilon }_{e\tau }$ using high-purity ${\nu }_{\mu }$ CC events at IceCube DeepCore