From the 1 of 23 linked papers with an AI index.
2 citations · 2 across the 4 of their papers we have counts for
15 papers · 1 filter
Results from the T2K experiment on neutrino mixing including a new far detector -like sample
The T2K Collaboration, K. Abe, S. Abe +404
We have made improved measurements of three-flavor neutrino mixing with 19.7(16.3) protons on target in (anti-)neutrino-enhanced beam modes. A new sample of muon-ne…
Fine-tuning final state interactions model in NuWro Monte Carlo event generator
Hemant Prasad, Jan T. Sobczyk, Rwik Dharmapal Banerjee +4
Recent experimental data from MINERvA on transverse kinematics observables across four different nuclear targets - carbon, oxygen, iron, and lead - have been utilized to refine the…
Re-optimization of a deep neural network model for electron-carbon scattering using new experimental data
Beata E. Kowal, Krzysztof M. Graczyk, Artur M. Ankowski +4
We present an updated deep neural network model for inclusive electron-carbon scattering. Using the bootstrap model [Phys.Rev.C 110 (2024) 2, 025501] as a prior, we incorporate rec…
Joint neutrino oscillation analysis from the T2K and NOvA experiments
NOvA, T2K Collaborations, : +597
The landmark discovery that neutrinos have mass and can change type (or "flavor") as they propagate -- a process called neutrino oscillation -- has opened up a rich array of theore…
Spectral function approach in NuWro: modeling of multinucleon final states in quasielastic scattering
Artur M. Ankowski, Rwik Dharmapal Banerjee, Jan T. Sobczyk +4
Neutrino-oscillation experiments performed in the few-GeV energy region create an urgent demand for a significant improvement in the accuracy of modeling of neutrino interactions w…
Electron-nucleus cross sections from transfer learning
Krzysztof M. Graczyk, Beata E. Kowal, Artur M. Ankowski +4
Transfer learning (TL) allows a deep neural network (DNN) trained on one type of data to be adapted for new problems with limited information. We propose to use the TL technique in…