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Abstract Neutrinos offer a unique window to the distant, high-energy universe. Several next-generation instruments are being designed and proposed to characterize the flux of TeV–EeV neutrinos. The projected physics reach of the detectors is often quantified with simulation studies. However, a complete Monte Carlo estimate of detector performance is costly from a computational perspective, restricting the number of detector configurations considered when designing the instruments. In this paper, we present a new Python-based software framework, toise , which forecasts the performance of a high-energy neutrino detector using parameterizations of the detector performance, such as the effective areas, angular and energy resolutions, etc. The framework can be used to forecast performance of a variety of physics analyses, including sensitivities to diffuse fluxes of neutrinos and sensitivity to both transient and steady state point sources. This parameterized approach reduces the need for extensive simulation studies in order to estimate detector performance, and allows the user to study the influence of single performance metrics, like the angular resolution, in isolation. The framework is designed to allow for multiple detector components, each with different responses and exposure times, and supports paramterization of both optical- and radio-Cherenkov (Askaryan) neutrino telescopes. In the paper, we describe the mathematical concepts behind toise and introduce the reader to the use of the framework.more » « less
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Abstract Name that Neutrino is a citizen science project where volunteers aid in classification of events for the IceCube Neutrino Observatory, an immense particle detector at the geographic South Pole. From March 2023 to September 2023, volunteers did classifications of videos produced from simulated data of both neutrino signal and background interactions.Name that Neutrino obtained more than 128,000 classifications by over 1800 registered volunteers that were compared to results obtained by a deep neural network machine-learning algorithm. Possible improvements for bothName that Neutrino and the deep neural network are discussed. -
IceCube_Collaboration (Ed.)
Abstract More than 10000 photomultiplier tubes (PMTs) with a diameter of 80 mm will be installed in multi-PMT Digital Optical Modules (mDOMs) of the IceCube Upgrade. These have been tested and pre-calibrated at two sites. A throughput of more than 1000 PMTs per week with both sites was achieved with a modular design of the testing facilities and highly automated testing procedures. The testing facilities can easily be adapted to other PMTs, such that they can, e.g., be re-used for testing the PMTs for IceCube-Gen2. Single photoelectron response, high voltage dependence, time resolution, prepulse, late pulse, afterpulse probabilities, and dark rates were measured for each PMT. We describe the design of the testing facilities, the testing procedures, and the results of the acceptance tests.
Free, publicly-accessible full text available July 1, 2025 -
Abstract The IceCube Neutrino Observatory relies on an array of photomultiplier tubes to detect Cherenkov light produced by charged particles in the South Pole ice. IceCube data analyses depend on an in-depth characterization of the glacial ice, and on novel approaches in event reconstruction that utilize fast approximations of photoelectron yields. Here, a more accurate model is derived for event reconstruction that better captures our current knowledge of ice optical properties. When evaluated on a Monte Carlo simulation set, the median angular resolution for in-ice particle showers improves by over a factor of three compared to a reconstruction based on a simplified model of the ice. The most substantial improvement is obtained when including effects of birefringence due to the polycrystalline structure of the ice. When evaluated on data classified as particle showers in the high-energy starting events sample, a significantly improved description of the events is observed.
Free, publicly-accessible full text available June 1, 2025 -
Neutrino oscillations at the highest energies and longest baselines can be used to study the structure of spacetime and test the fundamental principles of quantum mechanics. If the metric of spacetime has a quantum mechanical description, its fluctuations at the Planck scale are expected to introduce non-unitary effects that are inconsistent with the standard unitary time evolution of quantum mechanics. Neutrinos interacting with such fluctuations would lose their quantum coherence, deviating from the expected oscillatory flavour composition at long distances and high energies. Here we use atmospheric neutrinos detected by the IceCube South Pole Neutrino Observatory in the energy range of 0.5–10.0 TeV to search for coherence loss in neutrino propagation. We find no evidence of anomalous neutrino decoherence and determine limits on neutrino–quantum gravity interactions. The constraint on the effective decoherence strength parameter within an energy-independent decoherence model improves on previous limits by a factor of 30. For decoherence effects scaling as E2 , our limits are advanced by more than six orders of magnitude beyond past measurements compared with the state of the art.more » « lessFree, publicly-accessible full text available June 1, 2025