Related papers: Garvey-Kelson Relations for Nuclear Charge Radii
Nuclear masses are predicted with the Bayesian neural networks by learning the mass surface of even-even nuclei and the correlation energies to their neighbouring nuclei. By keeping the known physics in various sophisticated mass models and…
The radial basis function (RBF) approach is applied in predicting nuclear masses for 8 widely used nuclear mass models, ranging from macroscopic-microscopic to microscopic types. A significantly improved accuracy in computing nuclear masses…
The anisotropic kernel ridge regression (AKRR) approach in nuclear mass predictions is developed by introducing the anisotropic kernel function into the kernel ridge regression (KRR) approach, without introducing new weight parameter or…
Relativistic and unfactorized calculations for the nuclear transparency extracted from exclusive A(e,e'p) reactions for 0.3 \leq Q^2 \leq 10 (GeV/c)^2 are presented for the target nuclei C, Si, Fe and Pb. For Q^2 \geq 0.6 (GeV/c)^2, the…
The shell effect and isospin effect in nuclear charge radii are systematically investigated and a four-parameter formula is proposed for the description of the root-mean-square (rms) charge radii by combining the shell corrections and…
Nuclear masses play a crucial role in both nuclear physics and astrophysics, driving sustained efforts toward their precise experimental determination and reliable theoretical prediction. In this work, we compile the newly measured masses…
In this work, a refined Bayesian neural network (BNN) based approach with six inputs including the proton number, mass number, and engineered features associated with the pairing effect, shell effect, isospin effect, and ``abnormal" shape…
Relativistic mean-field models (RMF) based on the exchange of $\sigma$, $\omega$, and $\rho$ mesons including non-linear nucleon-$\sigma$ couplings and density-dependent $\rho$ coupling, are considered. A large set of models is generated…
We introduce a global nuclear mass formula which is based on the macroscopic-microscopic method, the Skyrme energy-density functional and the isospin symmetry in nuclear physics. The rms deviation with respect to 2149 known nuclear masses…
The qBounce collaboration built over the last years a new Ramsey-type Gravitational Resonance Spectroscopy (GRS) experiment. After commissioning between 2016 and 2018, the setup was able to measure the Ramsey transitions with GRS for the…
Charge radii of mirror nuclei are calculated by implementing pairing effects with the Hartree-Fock Bogoliubov approximation. Correlations between the difference of charge radii ($\Delta R_{ch}$) and slope of nuclear symmetry energy (L) are…
Distributions of transverse kinematic imbalance in neutrino-nucleus interactions in the few GeV regime are sensitive to nuclear effects. We present a study comparing the latest predictions of transverse kinematic imbalance from the…
The first determination of the nuclear charge radius by laser spectroscopy for a five-electron system is reported. This is achieved by combining high-accuracy ab initio mass-shift calculations and a high-resolution measurement of the…
New formulas to calculate the nuclear charge radii and the nuclear binding energies have been derived in the framework of an alpha-cluster model. The particular features of the model are two assumptions that the proton-neutron pair…
Kernel Regularized Least Squares (KRLS) is a popular method for flexibly estimating models that may have complex relationships between variables. However, its usefulness to many researchers is limited for two reasons. First, existing…
The root-mean-square (rms) nuclear charge radius of ^8He, the most neutron-rich of all particle-stable nuclei, has been determined for the first time to be 1.93(3) fm. In addition, the rms charge radius of ^6He was measured to be 2.068(11)…
There are several assumptions made in a standard $\chi^2$ analysis of data, including the frequent assumption that the likelihood function is well approximated by a multivariate Gaussian distribution. This article briefly reviews the…
We perform a global sensitivity analysis of the binding energy and the charge radius of the nucleus $^{16}$O to identify the most influential low-energy constants in the next-to-next-to-leading order chiral Hamiltonian with two- and…
We introduce a robust, interpretable machine learning (ML) framework that combines numerical regression for high-accuracy predictions with symbolic regression to uncover the underlying physics. This hybrid approach effciently derives…
We discuss the implications of recent experimental evidence of nuclear Short Range Correlations (SRCs) on the modeling of the wave function of complex nuclei. We perform a calculation of potential energy contributions of pp and pn pairs in…