Related papers: Modeling inclusive electron-nucleus scattering wit…
A quantitative understanding of the weak nuclear response is a prerequisite for the analyses of neutrino experiments such as K2K and MiniBOONE, which measure energy and angle of the muons produced in neutrino-nucleus interactions in the…
Developing a predictive capability for inelastic scattering will find applications in multiple areas. Experimental data for neutron-nucleus inelastic scattering is limited and thus one needs a robust theoretical framework to complement it.…
Uncertainty quantification for image data is dominated by complex deep learning methods, yet the field lacks an interpretable, mathematically grounded baseline. We propose Bayesian scattering to fill this gap, serving as a first-step…
The problem of electron-proton scattering is handed over both the elastic and inelastic scattering. Two models are presented in this sense. The first, depends on the multi photon exchange ladder diagram, where the transition matrix is…
We propose a novel approach to perform approximate Bayesian inference in complex models such as Bayesian neural networks. The approach is more scalable to large data than Markov Chain Monte Carlo, it embraces more expressive models than…
Antiproton-nucleon ($\bar{p}N$) total cross sections are typically 3-4 times larger than the $NN$ ones at incident energies from a few hundreds to thousands MeV. We investigate antiproton-nucleus scattering as it could work as a probe of…
Temperature dependence of the neutron-nucleus interaction is known as the Doppler broadening of the cross-sections. This is a well-known effect due to the thermal motion of the target nuclei that occurs in the neutron-nucleus interaction.…
I review the main features of the nuclear response extracted from electron scattering data. The emerging picture clearly shows that the shell model does not provide a fully quantitative description of nuclear dynamics. On the other hand,…
We perform a comprehensive analysis of complete fusion cross section data with the aim to derive, in a completely data-driven way, a model suitable to predict the integrated cross section of the fusion between light to medium mass nuclei at…
Modern nuclear data evaluation increasingly requires not only accurate scattering calculations, but also efficient methods for uncertainty quantification and parameter optimization, tasks that benefit from differentiable solvers amenable to…
This study investigates the application of an artificial neural network to predict the complex dielectric properties of granular catalysts commonly used in microwave reaction chemistry. The study utilizes finite element electromagnetic…
In recent years, many studies on neutrino-nucleus scattering have been carried out to investigate nuclear structures and the interactions between neutrinos and nucleons. This paper develops a charged-current quasielastic (CCQE)…
Proper interpretation of past, current, and future data on lepton-nucleus reactions requires a clear separation between quantum electrodynamics (QED) and strong interaction effects inside the nucleus. First studies of QED in-medium lepton…
Superscaling analyses of inclusive electron scattering from nuclei are extended from the quasielastic processes to the delta excitation region. The calculations of $(e,e^\prime)$ cross sections for the target nucleus $^{12}$C at various…
Semi-inclusive neutrino-nucleus scattering, corresponding to the simultaneous detection of a lepton and one or more hadrons in the final state, is shown to be much more sensitive to nuclear effects than the inclusive process. The…
We present a detailed study of a continuum random phase approximation approach to quasielastic electron-nucleus and neutrino-nucleus scattering. The formalism is validated by confronting ($e,e'$) cross-section predictions with electron…
Artificial Neural Networks are connectionist systems that perform a given task by learning on examples without having prior knowledge about the task. This is done by finding an optimal point estimate for the weights in every node.…
We propose a generic empirical formula for total inelastic cross-sections for various target nuclei scattered by a proton at different energies, which is applicable over a wide range of energy from $15 ~MeV$ to $1~ TeV$. The proposed model…
Achieving maximum scientific results from the overwhelming volume of astronomical data to be acquired over the next few decades will demand novel, fully automatic methods of data analysis. Artificial intelligence approaches hold great…
We present a parametrization of the observed enhancement in the transverse electron quasielastic (QE) response function for nucleons bound in carbon as a function of the square of the four momentum transfer (Q2) in terms of a correction to…