New Measurement of Muon Neutrino Disappearance from the IceCube Experiment

TL;DR

This paper reports a new measurement of muon neutrino disappearance using IceCube data from 2012 to 2021, employing CNNs for improved event reconstruction to study neutrino oscillations at energies below 100 GeV.

Contribution

It introduces the use of convolutional neural networks for event reconstruction in IceCube, enabling more precise measurements of atmospheric muon neutrino oscillations.

Findings

Preliminary results on muon neutrino disappearance.

Effective CNN-based event reconstruction method.

Data spanning nearly a decade analyzed.

Abstract

The IceCube Neutrino Observatory is a Cherenkov detector located at the South Pole. Its main component consists of an in-ice array of optical modules instrumenting one cubic kilometer of deep Glacial ice. The DeepCore sub-detector is a denser in-fill array with a lower energy threshold, allowing us to study atmospheric neutrinos oscillations with energy below 100 GeV arriving through the Earth. We present preliminary results of an atmospheric muon neutrino disappearance analysis using data from 2012 to 2021 and employing convolutional neural networks (CNNs) for precise and fast event reconstructions.