The IceCube Neutrino Observatory has established the existence of a high-energy all-sky neutrino flux of astrophysical origin. This discovery was made using events interacting within a fiducial region of the detector surrounded by an active veto and with reconstructed energy above 60 TeV, commonly known as the high-energy starting event sample (HESE). We revisit the analysis of the HESE sample with an additional 4.5 years of data, newer glacial ice models, and improved systematics treatment. This paper describes the sample in detail, reports on the latest astrophysical neutrino flux measurements, and presents a source search for astrophysical neutrinos. We give the compatibility of these observations with specific isotropic flux models proposed in the literature as well as generic power-law-like scenarios. Assuming ν e ∶ν μ ∶ν τ ¼ 1∶1∶1, and an equal flux of neutrinos and antineutrinos, we find that the astrophysical neutrino spectrum is compatible with an unbroken power law, with a preferred spectral index of 2.87 þ0.20 −0.19 for the 68% confidence interval.

The IceCube Neutrino Observatory at the South Pole has measured the diffuse astrophysical neutrino flux up to ∼PeV energies and is starting to identify first point source candidates. The next generation facility, IceCube-Gen2, aims at extending the accessible energy range to EeV in order to measure the continuation of the astrophysical spectrum, to identify neutrino sources, and to search for a cosmogenic neutrino flux. As part of IceCube-Gen2, a radio array is foreseen that is sensitive to detect Askaryan emission of neutrinos beyond ∼30 PeV. Surface and deep antenna stations have different benefits in terms of effective area, resolution, and the capability to reject backgrounds from cosmic-ray air showers and may be combined to reach the best sensitivity. The optimal detector configuration is still to be identified. This contribution presents the full-array simulation efforts for a combination of deep and surface antennas, and compares different design options with respect to their sensitivity to fulfill the science goals of IceCube-Gen2.

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We describe an improved in-situ calibration of the single-photoelectron charge distributions for each of the in-ice Hamamatsu Photonics R7081-02[MOD] photomultiplier tubes in the IceCube Neutrino Observatory. The characterization of the individual PMT charge distributions is important for PMT calibration, data and Monte Carlo simulation agreement, and understanding the effect of hardware differences within the detector. We discuss the single photoelectron identification procedure and how we extract the single-photoelectron charge distribution using a deconvolution of the multiple-photoelectron charge distribution. K : Detector modelling and simulations II (electric fields, charge transport, multiplication and induction, pulse formation, electron emission, etc); Photon detectors for UV, visible and IR photons (vacuum)

The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstruction tasks. Many of these applications have been adopted from other domains. However, data in the field of physics are unique in the context of machine learning, insofar as their generation process and the laws and symmetries they abide by are usually well understood. Most commonly used deep learning architectures fail at utilizing this available information. In contrast, more traditional likelihood-based methods are capable of exploiting domain knowledge, but they are often limited by computational complexity. In this contribution, a hybrid approach is presented that utilizes generative neural networks to approximate the likelihood, which may then be used in a traditional maximum-likelihood setting. Domain knowledge, such as invariances and detector characteristics, can easily be incorporated in this approach. The hybrid approach is illustrated by the example of event reconstruction in IceCube.

The IceCube Neutrino Observatory measures cosmic-ray air showers with both its surface array IceTop and its 1.5-2.5 km deep in-ice array. IceTop measures the charge deposited by electromagnetic particles and low-energy muons. The highly abundant electromagnetic particles mainly determine the cosmic ray primary energy, while the low-energy muons, visible at the edge of the shower, add a sensitivity to the primary composition. The high-energy (>300 GeV) muon bundle is studied through its energy loss profile in the in-ice detector. These muons provide information about the early interactions of the cosmic ray in the atmosphere and thus to the mass of the primary particle. In this work we combine all three pieces of information. Since the yield of low-and high-energy muons differs significantly among existing hadronic interaction models, this provides a unique sensitivity to model dependent variations in cosmic-ray air shower studies.

IceCube has discovered a flux of astrophysical neutrinos, and more recently has used muonneutrino datasets to present evidence for one source; a flaring blazar known as TXS 0506+056. However, the sources responsible for the majority of the astrophysical neutrino flux remain elusive. Opening up new channels for detection can improve sensitivity and increase the discovery potential. In this work we present a new neutrino dataset relying heavily on Deep-Neural-Networks (DNN) to select cascade events produced from neutral-current interactions of all flavors and charged-current interactions with flavors other than muon-neutrino. The speed of DNN processing makes it possible to select events in near realtime with a single GPU. Cascade events have reduced angular resolution when compared to muon-neutrino events, however the resulting dataset has a lower energy threshold in the southern sky and a lower background rate. These benefits lead to an factor of 2-3 improvement in sensitivity to sources in the Southern Sky when compared to muon-neutrino datasets. This dataset is particularly promising for identifying transient neutrino sources in the Southern Sky and neutrino production from the galactic plane.