activity
20152026
most citedSemantic Segmentation with a Sparse Convolutional Neural Network for Event Reconstruction in MicroBooNE

46 citations · 173 across the 30 of their papers we have counts for

collaborators
Showing 2024Show all

11 papers · 1 filter

hep-ex202410 cited

Search for an Anomalous Production of Charged-Current Interactions Without Visible Pions Across Multiple Kinematic Observables in MicroBooNE

MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana +177

This Letter presents an investigation of low-energy electron-neutrino interactions in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment, motivated by the excess of el…

hep-ex20243 cited

Data-driven model validation for neutrino-nucleus cross section measurements

MicroBooNE collaboration, P. Abratenko, O. Alterkait +184

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation paramet…

hep-ex202410 cited

Demonstration of new MeV-scale capabilities in large neutrino LArTPCs using ambient radiogenic and cosmogenic activity in MicroBooNE

MicroBooNE collaboration, P. Abratenko, O. Alterkait +184

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips,…

hep-ex2024

Demonstration of neutron identification in neutrino interactions in the MicroBooNE liquid argon time projection chamber

MicroBooNE collaboration, P. Abratenko, O. Alterkait +187

A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid ar…

hep-ex2024

Improving neutrino energy estimation of charged-current interaction events with recurrent neural networks in MicroBooNE

MicroBooNE collaboration, P. Abratenko, O. Alterkait +186

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture f…

hep-ex2024

Exploration of mass splitting and muon/tau mixing parameters for an eV-scale sterile neutrino with IceCube

R. Abbasi, M. Ackermann, J. Adams +421

We present the first three-parameter fit to a 3+1 sterile neutrino model using 7.634 years of data from the IceCube Neutrino Observatory on charged-current inter…