450 citations · 537 across the 6 of their papers we have counts for
6 papers
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…
Reconstructing Neutrino Energy using CNNs for GeV Scale IceCube Events
Jessie Micallef
Measurements of neutrinos at and below 10 GeV provide unique constraints of neutrino oscillation parameters as well as probes of potential Non-Standard Interactions (NSI). The IceC…
Study of Mass Composition of Cosmic Rays with IceTop and IceCube
Paras Koundal, Matthias Plum, Julian Saffer
The IceCube Neutrino Observatory is a multi-component detector at the South Pole which detects high-energy particles emerging from astrophysical events. These particles provide us…
All-flavor constraints on nonstandard neutrino interactions and generalized matter potential with three years of IceCube DeepCore data
IceCube Collaboration, R. Abbasi, M. Ackermann +370
We report constraints on nonstandard neutrino interactions (NSI) from the observation of atmospheric neutrinos with IceCube, limiting all individual coupling strengths from a singl…
Combined sensitivity to the neutrino mass ordering with JUNO, the IceCube Upgrade, and PINGU
Gen2 Collaboration, M. G. Aartsen, M. Ackermann +440
The ordering of the neutrino mass eigenstates is one of the fundamental open questions in neutrino physics. While current-generation neutrino oscillation experiments are able to pr…
Time-integrated Neutrino Source Searches with 10 years of IceCube Data
IceCube Collaboration, M. G. Aartsen, M. Ackermann +357
This paper presents the results from point-like neutrino source searches using ten years of IceCube data collected between Apr.~6, 2008 and Jul.~10, 2018. We evaluate the significa…