Related papers: Relativistic Mean-Field Hadronic Models under Nucl…
Multivariate analysis of fMRI data has benefited substantially from advances in machine learning. Most recently, a range of probabilistic latent variable models applied to fMRI data have been successful in a variety of tasks, including…
We propose a quantization procedure for the nucleon-scalar meson system, in which an arbitrary mean scalar meson field $\phi$ is introduced. The equivalence of this procedure with the usual ones is proven for any given value of $\phi$. By…
We analytically derive mean-field models for all-to-all coupled networks of heterogeneous, adapting, two-dimensional integrate and fire neurons. The class of models we consider includes the Izhikevich, adaptive exponential, and quartic…
A systematic study of the ground-state properties of even-even rare earth nuclei has been performed in the framework of the Relativistic Mean-Field (RMF) theory using the parameter set NL-SH. Nuclear radii, isotope shifts and deformation…
We consider the tuning parameter selection rules for nuclear norm regularized multivariate linear regression (NMLR) in high-dimensional setting. High-dimensional multivariate linear regression is widely used in statistics and machine…
Nuclear magnetic resonance (NMR) technique benefits from high magnetic field not only due to the field-enhanced measurement sensitivity and resolution, but also because it is a powerful tool to investigate field-induced physics in modern…
Spatial symmetries and invariances play an important role in the behaviour of materials and should be respected in the description and modelling of material properties. The focus here is the class of physically symmetric and positive…
Single--particle spectra of $\Lambda $ and $\Sigma $ hypernuclei are calculated within a relativistic mean--field theory. The hyperon couplings used are compatible with the $\Lambda $ binding in saturated nuclear matter, neutron-star masses…
Asymmetric nuclear matter is investigated in the low density region below the nuclear saturation density. Microscopic calculations based on the Dirac Brueckner Hartree-Fock (DBHF) approach with realistic nucleon-nucleon potentials are used…
We investigate how vector-isoscalar and vector-isovector interactions can be determined within the density regime of neutron stars (NSs), while fulfilling nuclear and astrophysics constrains. We make use of the Chiral Mean Field (CMF)…
In this paper we consider a model for a nucleon interacting with the $\omega$ and $\sigma$ mesons in the atomic nucleus. The model is relativistic, but we study it in the nuclear physics nonrelativistic limit, which is of a very different…
The properties of asymmetric nuclear matter have been investigated in a relativistic Dirac-Brueckner-Hartree-Fock framework using the Bonn A potential. The components of the self-energies are extracted by projecting on Lorentz invariant…
Neural Radiance Fields (NeRFs) have emerged as a groundbreaking paradigm for representing 3D objects and scenes by encoding shape and appearance information into the weights of a neural network. Recent studies have demonstrated that these…
We construct parameter sets of the relativistic mean-field model fitted to the recent constraints on the asymmetry energy $J$ and the slope parameter $L$ for pure neutron matter. We find cases of unphysical behaviour, i.e.\ the appearance…
Nuclear matter and neutron stars are studied in the framework of an extended relativistic mean-field (RMF) model with higher-order derivative and density dependent couplings of nucleons to the meson fields. The derivative couplings lead to…
We propose a new segmentation model combining common regularization energies, e.g. Markov Random Field (MRF) potentials, and standard pairwise clustering criteria like Normalized Cut (NC), average association (AA), etc. These clustering and…
Neural Radiance Fields (NeRF) show impressive performance in photo-realistic free-view rendering of scenes. Recent improvements on the NeRF such as TensoRF and ZipNeRF employ explicit models for faster optimization and rendering, as…
The composition and properties of infinite nuclear matter under extreme conditions of temperature and pressure remain incompletely understood. In this work, we constrain the equation of state (EoS) of nuclear matter - constructed within the…
We develop a chiral symmetric relativistic mean field model with logarithmic sigma potential derived in the strong coupling limit of the lattice QCD. We find that both of the nuclear matter and finite nuclei are well described in the…
Properties of nuclear matter are investigated in the framework of relativistic Brueckner-Hartree-Fock model with the latest high-precision charge-dependent Bonn (pvCD-Bonn) potentials, where the coupling between pion and nucleon is adopted…