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The Radio Neutrino Observatory in Greenland (RNO-G) is the first in-ice radio array in the northern hemisphere for the detection of ultra-high energy neutrinos via the coherent radio emission from neutrino-induced particle cascades within the ice. The array is currently in phased construction near Summit Station on the Greenland ice sheet, with 7 stations deployed during the first two boreal summer field seasons of 2021 and 2022. In this paper, we describe the installation and system design of these initial RNO-G stations, and discuss the performance of the array as of summer 2024. 

This paper describes how intentional and unintentional radio emission from airplanes is recorded with the Radio Neutrino Observatory Greenland (RNO-G). We characterize the received signals and define a procedure to extract a clean set of impulsive signals. These signals are highly suitable for instrument calibration, also for future experiments. A set of signals is used to probe the timing precision of RNO-G in-situ, which is found to match expectations. We also discuss the impact of these signals on the ability to detect neutrinos with RNO-G. 

Abstract IceCube is a Cherenkov detector instrumenting over a cubic kilometer of glacial ice deep under the surface of the South Pole. The DeepCore sub-detector lowers the detection energy threshold to a few GeV, enabling the precise measurements of neutrino oscillation parameters with atmospheric neutrinos. The reconstruction of neutrino interactions inside the detector is essential in studying neutrino oscillations. It is particularly challenging to reconstruct sub-100 GeV events with the IceCube detectors due to the relatively sparse detection units and detection medium. Convolutional neural networks (CNNs) are broadly used in physics experiments for both classification and regression purposes. This paper discusses the CNNs developed and employed for the latest IceCube-DeepCore oscillation measurements [1]. These CNNs estimate various properties of the detected neutrinos, such as their energy, direction of arrival, interaction vertex position, flavor-related signature, and are also used for background classification. 

Abstract The IceCube Neutrino Observatory, instrumenting about 1 km³of deep, glacial ice at the geographic South Pole, is due to be enhanced with the IceCube Upgrade. The IceCube Upgrade, to be deployed during the 2025/26 Antarctic summer season, will consist of seven new strings of photosensors, densely embedded near the bottom center of the existing array. Aside from a world-leading sensitivity to neutrino oscillations, a primary goal is the improvement of the calibration of the optical properties of the instrumented ice. This calibration will be applied to the entire archive of IceCube data, improving the angular and energy resolution of the detected neutrino events. For this purpose, the Upgrade strings include a host of new calibration devices. Aside from dedicated calibration modules, several thousand LED flashers have been incorporated into the photosensor modules. We describe the design, production, and testing of these LED flashers before their integration into the sensor modules as well as the use of the LED flashers during lab testing of assembled sensor modules.