Calibration LEDs in the IceCube Upgrade D-Egg Modules

TL;DR

This paper discusses the calibration of optical sensors in IceCube Upgrade modules, focusing on measuring the optical properties of refrozen ice using LED calibration systems to improve neutrino detection accuracy.

Contribution

It introduces a simulation method for calibrating the hole ice properties in IceCube modules using LED systems, enhancing neutrino reconstruction accuracy.

Findings

Calibration method accurately recovers hole ice properties

Simulation results match Monte Carlo truth

Improves understanding of ice optical properties

Abstract

The IceCube Upgrade, planned for deployment in the 2022/2023 South Pole Summer, will involve deployment of a greater density of optical modules (vertically spaced ~3 m). Improvements in the calibration of optical sensors and an enhanced understanding of the optical properties of the deep glacial ice, due to the more closely-spaced modules, are projected to have a large impact on neutrino reconstruction. A new optical sensor module called the "Dual optical sensors in an Ellipsoid glass for Gen2" (D-Egg), is planned for installation in both the IceCube Upgrade and IceCube-Gen2, and has both an upward and downward facing 8" high quantum efficiency PMT. The D-Egg modules will make use of a downward-facing LED calibration system to measure the optical properties of the refrozen drill holes ("hole ice"). An inner section of the hole ice contains some impurities, which modify the optical properties of the ice; this area is known as the "bubble column". The measurement of this "hole ice" is critical both for the upgraded IceCube detector as well as the current generation IceCube, as refrozen ice contributes significant systematic uncertainties to the reconstruction of low energy neutrinos. A simulation was performed, where the size and optical properties of the bubble column were varied. A log likelihood function is constructed from the geometry of the D-Eggs and properties of the hole ice. The minimization recovers best fit values close to the Monte Carlo truth.