From PeV to TeV: Astrophysical Neutrinos with Contained Vertices in 10 years of IceCube Data

The IceCube Neutrino Observatory is a cubic-kilometer Cherenkov detector at the South Pole, designed to study neutrinos of astrophysical origin. We present an analysis of the Medium Energy Starting Events (MESE) sample, a veto-based event selection that selects neutrinos and efficiently rejects a background of cosmic ray-induced muons This is an extension of the High Energy Starting Event (HESE) analysis, which established the existence of high-energy neutrinos of astrophysical origin. The HESE sample is consistent with a single power law spectrum with best-fit index $2.87^{+0.20}_{-0.19}$, which is softer than complementary IceCube measurements of the astrophysical neutrino spectrum. While HESE is sensitive to neutrinos above 60 TeV, MESE improves the sensitivity to lower energies, down to 1 TeV. In this analysis we use an improved understanding of atmospheric backgrounds in the astrophysical neutrino sample via more accurate modeling of the detector self-veto. A previous measurement with a 2-year MESE dataset had indicated the presence of a possible 30 TeV excess. With 10 years of data, we have a larger sample size to investigate this excess. We will use this event selection to measure the cosmic neutrino energy spectrum over a wide energy range. The flavor ratio of astrophysical neutrinos will also be discussed.Comment: Presented at the 38th International Cosmic Ray Conference (ICRC2023). See arXiv:2307.13047 for all IceCube contribution

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

NeuroBench:Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

Non-standard neutrino interactions in IceCube

Non-standard neutrino interactions (NSI) may arise in various types of new physics. Their existence would change the potential that atmospheric neutrinos encounter when traversing Earth matter and hence alter their oscillation behavior. This imprint on coherent neutrino forward scattering can be probed using high-statistics neutrino experiments such as IceCube and its low-energy extension, DeepCore. Both provide extensive data samples that include all neutrino flavors, with oscillation baselines between tens of kilometers and the diameter of the Earth. DeepCore event energies reach from a few GeV up to the order of 100 GeV - which marks the lower threshold for higher energy IceCube atmospheric samples, ranging up to 10 TeV. In DeepCore data, the large sample size and energy range allow us to consider not only flavor-violating and flavor-nonuniversal NSI in the μ−τ sector, but also those involving electron flavor. The effective parameterization used in our analyses is independent of the underlying model and the new physics mass scale. In this way, competitive limits on several NSI parameters have been set in the past. The 8 years of data available now result in significantly improved sensitivities. This improvement stems not only from the increase in statistics but also from substantial improvement in the treatment of systematic uncertainties, background rejection and event reconstruction

IceCube Search for Earth-traversing ultra-high energy Neutrinos

The search for ultra-high energy neutrinos is more than half a century old. While the hunt for these neutrinos has led to major leaps in neutrino physics, including the detection of astrophysical neutrinos, neutrinos at the EeV energy scale remain undetected. Proposed strategies for the future have mostly been focused on direct detection of the first neutrino interaction, or the decay shower of the resulting charged particle. Here we present an analysis that uses, for the first time, an indirect detection strategy for EeV neutrinos. We focus on tau neutrinos that have traversed Earth, and show that they reach the IceCube detector, unabsorbed, at energies greater than 100 TeV for most trajectories. This opens up the search for ultra-high energy neutrinos to the entire sky. We use ten years of IceCube data to perform an analysis that looks for secondary neutrinos in the northern sky, and highlight the promise such a strategy can have in the next generation of experiments when combined with direct detection techniques

Posteriori analysis on IceCube double pulse tau neutrino candidates

The IceCube Neutrino Observatory at the South Pole detects Cherenkov light emitted by charged secondary particles created by primary neutrino interactions. Double pulse waveforms can arise from charged current interactions of astrophysical tau neutrinos with nucleons in the ice and the subsequent decay of tau leptons. The previous 8-year tau double pulse analysis found three tau neutrino candidate events. Among them, the most promising one observed in 2014 is located very near the dust layer in the middle of the detector. A posterior analysis on this event will be presented in this paper, using a new ice model treatment with continuously varying nuisance parameters to do the targeted Monte Carlo re-simulation for tau and other background neutrino ensembles. The impact of different ice models on the expected signal and background statistics will also be discussed