Related papers: Modeling inclusive electron-nucleus scattering wit…
Accurate modeling of neutron-induced (n,p) reaction cross sections is essential for diverse applications in nuclear physics, including reactor design, nuclear astrophysics, and radionuclide production. However, experimental data are often…
Recent advances in electron microscopy allowed the generation of high-energy electron wave packets of ultrashort duration. Here we present a non-perturbative S-matrix theory for scattering of ultrashort electron wave packets by atomic…
Inverse scattering problems are inherently challenging, given the fact they are ill-posed and nonlinear. This paper presents a powerful deep learning-based approach that relies on generative adversarial networks to accurately and…
Machine learning interatomic potentials are revolutionizing large-scale, accurate atomistic modelling in material science and chemistry. Many potentials use atomic cluster expansion or equivariant message passing frameworks. Such frameworks…
Small-angle X-ray and neutron scattering are widely used to investigate soft matter and biophysical systems. The experimental errors are essential when assessing how well a hypothesized model fits the data. Likewise, they are important when…
We construct a model for inelastic neutrino- and electron-nucleon scattering cross sections using effective leading order parton distribution functions with a new scaling variable $\xi_w$. Non-perturbative effects are well described using…
Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model…
A detailed study of charged current quasielastic neutrino and antineutrino scattering cross sections on a $^{12}$C target with no pions in the final state is presented. The initial nucleus is described by means of a realistic spectral…
Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of interest, while temporal profiles of subjects commonly follow a…
We present quasi-elastic neutrino-nucleus cross sections in the energy range from 150 MeV up to 5 GeV for the target nuclei 12C and 56Fe. A relativistic description of the nuclear dynamics and the neutrino-nucleus coupling is adopted. For…
In the impulse approximation regime the nuclear response to a weakly interacting probe can be written in terms of the measured nucleon structure fuctions and the target spectral function, yielding the energy and momentum distribution of the…
Experiment E02-019, performed in Hall C at the Thomas Jefferson National Accelerator Facility (TJNAF), was a measurement of inclusive electron cross sections for several nuclei ($^{2}$H,$^{3}$He, $^{4}$He, $^{9}$Be,$^{12}$C, $^{63}$Cu, and…
Based on an analysis of the short range chemical environment of each atom in a system, standard machine learning based approaches to the construction of interatomic potentials aim at determining directly the central quantity which is the…
Inverse problems and, in particular, inferring unknown or latent parameters from data are ubiquitous in engineering simulations. A predominant viewpoint in identifying unknown parameters is Bayesian inference where both prior information…
Progress in neutrino-nucleus cross section models is being driven by the need for highly accurate predictions for the neutrino oscillation community. These sophisticated models are being developed within a microscopic description of the…
The Bayesian approach for the feed-forward neural networks is reviewed. Its potential for usage in hadron physics is discussed. As an example of the application the study of the the two-photon exchange effect is presented. We focus on the…
We present a short overview on the studies of transverse momentum dependent parton distribution functions of the nucleon. The aim of such studies is to provide a three dimensional imagining of the nucleon and a comprehensive description of…
The task of clustering a set of objects based on multiple sources of data arises in several modern applications. We propose an integrative statistical model that permits a separate clustering of the objects for each data source. These…
Theoretical predictions for elastic neutrino-electron scattering have no hadronic or nuclear uncertainties at leading order making this process an important tool for normalizing neutrino flux. However, the process is subject to large…
A model for elastic scattering of nucleons (and anti-nucleons) based on the quark-diquark representation of the nucleon with springy Pomeron, providing increased real part of the scattering amplitude, is developed. The model predictions are…