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19982026
most citedFirst Results from KamLAND: Evidence for Reactor Anti-Neutrino Disappearance

2.7k citations · 27.3k across the 288 of their papers we have counts for

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Showing 2020Show all

21 papers · 1 filter

physics.comp-ph2020★ 24 cited

LeptonInjector and LeptonWeighter: A neutrino event generator and weighter for neutrino observatories

R. Abbasi, M. Ackermann, J. Adams +362

We present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino…

hep-ex2020★ 49 cited

Measurement of the high-energy all-flavor neutrino-nucleon cross section with IceCube

R. Abbasi, M. Ackermann, J. Adams +361

The flux of high-energy neutrinos passing through the Earth is attenuated due to their interactions with matter. The interaction rate is modulated by the neutrino interaction cross…

astro-ph.HE2020★ 380 cited

The IceCube high-energy starting event sample: Description and flux characterization with 7.5 years of data

R. Abbasi, M. Ackermann, J. Adams +362

The IceCube Neutrino Observatory has established the existence of a high-energy all-sky neutrino flux of astrophysical origin. This discovery was made using events interacting with…

astro-ph.HE2020★ 8 cited

First all-flavor search for transient neutrino emission using 3-years of IceCube DeepCore data

R. Abbasi, M. Ackermann, J. Adams +359

Since the discovery of a flux of high-energy astrophysical neutrinos, searches for their origins have focused primarily at TeV-PeV energies. Compared to sub-TeV searches, high-ener…

hep-ex2020★ 47 cited

Detection of astrophysical tau neutrino candidates in IceCube

R. Abbasi, M. Ackermann, J. Adams +361

High-energy tau neutrinos are rarely produced in atmospheric cosmic-ray showers or at cosmic particle accelerators, but are expected to emerge during neutrino propagation over cosm…

physics.ins-det2020★ 25 cited

Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment

NEXT Collaboration, M. Kekic, C. Adams +88

Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high energy physics. In this paper, we attempt…