Related papers: A Data-Driven Density Functional Model for Nuclear…
Predictions of nuclear properties far from measured data are inherently imprecise because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model…
We study a particular class of relativistic nuclear energy density functionals in which only nucleon degrees of freedom are explicitly used in the construction of effective interaction terms. Short-distance (high-momentum) correlations, as…
Two of the most widely used electronic structure theory methods, namely Hartree-Fock and Kohn-Sham density functional theory, both requires the iterative solution of a set of Schr\"odinger-like equations. The speed of convergence of such…
The data-driven Bayesian model averaging is a rigorous statistical approach to combining multiple models for a unified prediction. Compared with the individual model, it provides more reliable information, especially for problems involving…
We have used the notion of the constituent quark model of nucleon, where a constituent quark carries its own internal structure, and applied it to determine nuclear structure functions ratios. It is found that the description of…
Radii of charge and neutron distributions are fundamental nuclear properties. They depend on both nuclear interaction parameters related to the equation of state of infinite nuclear matter and on quantal shell effects, which are strongly…
A sensitive correlation between the ground-state properties of light kaonic nuclei and the symmetry energy at high densities is constructed under the framework of relativistic mean-field theory. Taking oxygen isotopes as an example, we see…
Using a Deep Neuronal Network model (DNN) trained on the large ANI-1 data set of small organic molecules, we propose a transferable density-free many-body dispersion model (DNN-MBD). The DNN strategy bypasses the explicit Hirshfeld…
Expressing explicitly the parameters of the standard Skyrme interaction in terms of the macroscopic properties of asymmetric nuclear matter, we show in the Skyrme-Hartree-Fock approach that unambiguous correlations exist between observables…
Precise knowledge of the nuclear symmetry energy can be tentatively calibrated through multimessenger constraints. The neutron skin thickness of a heavy nucleus is one of the most sensitive indicators for probing the isovector components of…
The formation of $\alpha$-particle clusters on the surface of heavy nuclei is described in a generalized relativistic mean-field model with explicit cluster degrees of freedom. The effects on the size of the neutron skin of Sn nuclei and…
We investigate the density distributions of finite nuclei employing a well-designed deep neural network method. We calculate the target nucleon density distributions with Skyrme density functional theories, which are used to train the…
In recent years, several successful applications of the Artificial Neural Networks (ANNs) have emerged in nuclear physics and high-energy physics, as well as in biology, chemistry, meteorology, and other fields of science. A major goal of…
We investigate possible correlations between the stiffness of the symmetry energy at saturation density, the so-called $L$ parameter, and the neutron skin thickness of ${^{48}}$Ca and ${^{208}}$Pb, for which the recent measurements from the…
We build and train the artificial neural network model (ANN) based on the experimental $\alpha$-decay energy ($Q_{\alpha}$) data. Besides decays between the ground states of parent and daughter nuclei, decays from the ground state of parent…
Background: A global description of the ground-state properties of nuclei in a wide mass range in a unified manner is desirable not only for understanding exotic nuclei but for providing nuclear data for applications. Purpose: We…
The Kohn-Sham scheme of density functional theory is one of the most widely used methods to solve electronic structure problems for a vast variety of atomistic systems across different scientific fields. While the method is fast relative to…
Motivated by recent parity violating electron scattering experiments, we compute the Neutron Skin Thickness (NST) of nuclei modelled as (quantized) Skyrmions, the topological solitons of the Skyrme model. We show how in a certain…
[Background] We constructed the Kyushu chiral $g$-matrix and confirmed its reliability at $30 \lesssim E_{\rm in} \lesssim 100 $~MeV and $250 \lesssim E_{\rm in} \lesssim 400$~MeV for $^{12}$C scattering. Reaction cross section data of…
The KIDS framework for the nuclear equation of state (EoS) and energy density functional (EDF) offers the possibility to explore systematically the effect of EoS parameters on predictions for a variety of observables. The EoS parameters can…