activity
20142022
most citedTime-integrated Neutrino Source Searches with 10 years of IceCube Data

450 citations · 1.7k across the 23 of their papers we have counts for

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Showing 2021Show all

11 papers · 1 filter

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…

hep-ex2021★ 41 cited

Search for Quantum Gravity Using Astrophysical Neutrino Flavour with IceCube

R. Abbasi, M. Ackermann, J. Adams +378

Along their long propagation from production to detection, neutrino states undergo quantum interference which converts their types, or flavours. High-energy astrophysical neutrinos…

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★ 2 cited

KM3NeT/ARCA expectations in view of a novel multimessenger study of starburst galaxies

Antonio Marinelli, Antonio Ambrosone, Walid Idrissi Ibnsalih +4

Starburst galaxies (SBGs) and more in general starforming galaxies represent a class of galaxies with a high star formation rate (up to 100 solar masses/year). Despite their low lu…

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…