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The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth’s atmosphere, is unknown. Because of deflection by interstellar magnetic fields, cosmic rays produced within the Milky Way arrive at Earth from random directions. However, cosmic rays interact with matter near their sources and during propagation, which produces high-energy neutrinos. We searched for neutrino emission using machine learning techniques applied to 10 years of data from the IceCube Neutrino Observatory. By comparing diffuse emission models to a background-only hypothesis, we identified neutrino emission from the Galactic plane at the 4.5σ level of significance. The signal is consistent with diffuse emission of neutrinos from the Milky Way but could also arise from a population of unresolved point sources.

 

Abstract Galactic PeV cosmic-ray accelerators (PeVatrons) are Galactic sources theorized to accelerate cosmic rays up to PeV in energy. The accelerated cosmic rays are expected to interact hadronically with nearby ambient gas or the interstellar medium, resulting in γ -rays and neutrinos. Recently, the Large High Altitude Air Shower Observatory (LHAASO) identified 12 γ -ray sources with emissions above 100 TeV, making them candidates for PeVatrons. While at these high energies the Klein–Nishina effect exponentially suppresses leptonic emission from Galactic sources, evidence for neutrino emission would unequivocally confirm hadronic acceleration. Here, we present the results of a search for neutrinos from these γ -ray sources and stacking searches testing for excess neutrino emission from all 12 sources as well as their subcatalogs of supernova remnants and pulsar wind nebulae with 11 yr of track events from the IceCube Neutrino Observatory. No significant emissions were found. Based on the resulting limits, we place constraints on the fraction of γ -ray flux originating from the hadronic processes in the Crab Nebula and LHAASO J2226+6057. 

Abstract Gamma-ray bursts (GRBs) are considered as promising sources of ultra-high-energy cosmic rays (UHECRs) due to their large power output. Observing a neutrino flux from GRBs would offer evidence that GRBs are hadronic accelerators of UHECRs. Previous IceCube analyses, which primarily focused on neutrinos arriving in temporal coincidence with the prompt gamma-rays, found no significant neutrino excess. The four analyses presented in this paper extend the region of interest to 14 days before and after the prompt phase, including generic extended time windows and targeted precursor searches. GRBs were selected between 2011 May and 2018 October to align with the data set of candidate muon-neutrino events observed by IceCube. No evidence of correlation between neutrino events and GRBs was found in these analyses. Limits are set to constrain the contribution of the cosmic GRB population to the diffuse astrophysical neutrino flux observed by IceCube. Prompt neutrino emission from GRBs is limited to ≲1% of the observed diffuse neutrino flux, and emission on timescales up to 10 4 s is constrained to 24% of the total diffuse flux. 

Abstract Galaxy clusters have the potential to accelerate cosmic rays (CRs) to ultrahigh energies via accretion shocks or embedded CR acceleration sites. The CRs with energies below the Hillas condition will be confined within the cluster and eventually interact with the intracluster medium gas to produce secondary neutrinos and gamma rays. Using 9.5 yr of muon neutrino track events from the IceCube Neutrino Observatory, we report the results of a stacking analysis of 1094 galaxy clusters with masses ≳10 14 M ⊙ and redshifts between 0.01 and ∼1 detected by the Planck mission via the Sunyaev–Zel’dovich effect. We find no evidence for significant neutrino emission and report upper limits on the cumulative unresolved neutrino flux from massive galaxy clusters after accounting for the completeness of the catalog up to a redshift of 2, assuming three different weighting scenarios for the stacking and three different power-law spectra. Weighting the sources according to mass and distance, we set upper limits at a 90% confidence level that constrain the flux of neutrinos from massive galaxy clusters (≳10 14 M ⊙ ) to be no more than 4.6% of the diffuse IceCube observations at 100 TeV, assuming an unbroken E −2.5 power-law spectrum. 

Abstract The majority of astrophysical neutrinos have undetermined origins. The IceCube Neutrino Observatory has observed astrophysical neutrinos but has not yet identified their sources. Blazars are promising source candidates, but previous searches for neutrino emission from populations of blazars detected in ≳GeV gamma rays have not observed any significant neutrino excess. Recent findings in multimessenger astronomy indicate that high-energy photons, coproduced with high-energy neutrinos, are likely to be absorbed and reemitted at lower energies. Thus, lower-energy photons may be better indicators of TeV–PeV neutrino production. This paper presents the first time-integrated stacking search for astrophysical neutrino emission from MeV-detected blazars in the first Fermi Large Area Telescope low energy (1FLE) catalog using ten years of IceCube muon–neutrino data. The results of this analysis are found to be consistent with a background-only hypothesis. Assuming an E −2 neutrino spectrum and proportionality between the blazars MeV gamma-ray fluxes and TeV–PeV neutrino flux, the upper limit on the 1FLE blazar energy-scaled neutrino flux is determined to be 1.64 × 10 −12 TeV cm −2 s −1 at 90% confidence level. This upper limit is approximately 1% of IceCube’s diffuse muon–neutrino flux measurement. 

Abstract The reconstruction of event-level information, such as the direction or energy of a neutrino interacting in IceCube DeepCore, is a crucial ingredient to many physics analyses. Algorithms to extract this high level information from the detector’s raw data have been successfully developed and used for high energy events. In this work, we address unique challenges associated with the reconstruction of lower energy events in the range of a few to hundreds of GeV and present two separate, state-of-the-art algorithms. One algorithm focuses on the fast directional reconstruction of events based on unscattered light. The second algorithm is a likelihood-based multipurpose reconstruction offering superior resolutions, at the expense of larger computational cost. 

Abstract We present the first comprehensive search for high-energy neutrino emission from high- and low-mass X-ray binaries conducted by IceCube. Galactic X-ray binaries are long-standing candidates for the source of Galactic hadronic cosmic rays and neutrinos. The compact object in these systems can be the site of cosmic-ray acceleration, and neutrinos can be produced by interactions of cosmic rays with radiation or gas, in the jet of a microquasar, in the stellar wind, or in the atmosphere of the companion star. We study X-ray binaries using 7.5 yr of IceCube data with three separate analyses. In the first, we search for periodic neutrino emission from 55 binaries in the Northern Sky with known orbital periods. In the second, the X-ray light curves of 102 binaries across the entire sky are used as templates to search for time-dependent neutrino emission. Finally, we search for time-integrated emission of neutrinos for a list of 4 notable binaries identified as microquasars. In the absence of a significant excess, we place upper limits on the neutrino flux for each hypothesis and compare our results with theoretical predictions for several binaries. In addition, we evaluate the sensitivity of the next generation neutrino telescope at the South Pole, IceCube-Gen2, and demonstrate its power to identify potential neutrino emission from these binary sources in the Galaxy. 

Abstract We present a measurement of the high-energy astrophysical muon–neutrino flux with the IceCube Neutrino Observatory. The measurement uses a high-purity selection of 650k neutrino-induced muon tracks from the northern celestial hemisphere, corresponding to 9.5 yr of experimental data. With respect to previous publications, the measurement is improved by the increased size of the event sample and the extended model testing beyond simple power-law hypotheses. An updated treatment of systematic uncertainties and atmospheric background fluxes has been implemented based on recent models. The best-fit single power-law parameterization for the astrophysical energy spectrum results in a normalization of ϕ @ 100 TeV ν μ + ν ¯ μ = 1.44 − 0.26 + 0.25 × 10 − 18 GeV − 1 cm − 2 s − 1 sr − 1 and a spectral index γ SPL = 2.37 − 0.09 + 0.09 , constrained in the energy range from 15 TeV to 5 PeV. The model tests include a single power law with a spectral cutoff at high energies, a log-parabola model, several source-class-specific flux predictions from the literature, and a model-independent spectral unfolding. The data are consistent with a single power-law hypothesis, however, spectra with softening above one PeV are statistically more favorable at a two-sigma level. 

Abstract Ultraluminous infrared galaxies (ULIRGs) have infrared luminosities L IR ≥ 10 12 L ⊙ , making them the most luminous objects in the infrared sky. These dusty objects are generally powered by starbursts with star formation rates that exceed 100 M ⊙ yr −1 , possibly combined with a contribution from an active galactic nucleus. Such environments make ULIRGs plausible sources of astrophysical high-energy neutrinos, which can be observed by the IceCube Neutrino Observatory at the South Pole. We present a stacking search for high-energy neutrinos from a representative sample of 75 ULIRGs with redshift z ≤ 0.13 using 7.5 yr of IceCube data. The results are consistent with a background-only observation, yielding upper limits on the neutrino flux from these 75 ULIRGs. For an unbroken E −2.5 power-law spectrum, we report an upper limit on the stacked flux Φ ν μ + ν ¯ μ 90 % = 3.24 × 10 − 14 TeV − 1 cm − 2 s − 1 ( E / 10 TeV ) − 2.5 at 90% confidence level. In addition, we constrain the contribution of the ULIRG source population to the observed diffuse astrophysical neutrino flux as well as model predictions.