103 citations · 329 across the 15 of their papers we have counts for
6 papers · 1 filter
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…
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…
Transfer Learning for Neutrino Scattering: Domain Adaptation with GANs
Jose L. Bonilla, Krzysztof M. Graczyk, Artur M. Ankowski +4
Transfer learning (TL) is used to extrapolate the physics information encoded in a Generative Adversarial Network (GAN) trained on synthetic neutrino-carbon inclusive scattering da…
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…
Generative adversarial neural networks for simulating neutrino interactions
Jose L. Bonilla, Krzysztof M. Graczyk, Artur M. Ankowski +4
We propose a new approach to simulate neutrino scattering events as an alternative to the standard Monte Carlo generator approach. Generative adversarial neural network (GAN) model…
Developments in NuWro Monte Carlo generator
Hemant Prasad, Jan T. Sobczyk, Artur M. Ankowski +4
In this article, we highlight physics improvements in the NuWro Monte Carlo event generator. The upcoming version of NuWro will incorporate the integration of the argon spectral fu…