activity
20102025
most citedImproved Characterization of the Astrophysical Muon-Neutrino Flux with 9.5 Years of IceCube Data

241 citations · 1.1k across the 24 of their papers we have counts for

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17 papers · 1 filter

astro-ph.HE2025★ 1 cited

Prompt Searches for Very-High-Energy γ-Ray Counterparts to IceCube Astrophysical Neutrino Alerts

J. Abhir, A. Biland, K. Brand +817

The search for sources of high-energy astrophysical neutrinos can be significantly advanced through a multi-messenger approach, which seeks to detect the gamma rays that accompany…

astro-ph.HE2022★ 26 cited

Search for Astrophysical Neutrinos from 1FLE Blazars with IceCube

R. Abbasi, M. Ackermann, J. Adams +379

The majority of astrophysical neutrinos have undetermined origins. The IceCube Neutrino Observatory has observed astrophysical neutrinos but has not yet identified their sources. B…

astro-ph.HE2021★ 241 cited

Improved Characterization of the Astrophysical Muon-Neutrino Flux with 9.5 Years of IceCube Data

R. Abbasi, M. Ackermann, J. Adams +376

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-i…

astro-ph.HE2021★ 46 cited

A search for neutrino emission from cores of Active Galactic Nuclei

R. Abbasi, M. Ackermann, J. Adams +376

The sources of the majority of the high-energy astrophysical neutrinos observed with the IceCube neutrino telescope at the South Pole are unknown. So far, only a gamma-ray blazar w…

astro-ph.HE2021★ 28 cited

Search for multi-flare neutrino emissions in 10 years of IceCube data from a catalog of sources

IceCube collaboration, R. Abbasi, M. Ackermann +375

A recent time-integrated analysis of a catalog of 110 candidate neutrino sources revealed a cumulative neutrino excess in the data collected by IceCube between April 6, 2008 and Ju…

astro-ph.HE2021★ 18 cited

Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube

Mirco Hünnefeld

The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstru…