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Models based on nuclear energy density functionals can provide access to a multitude of observables for thousands of nuclei in a single framework with microscopic foundations. Such models can rival the accuracy of more phenomenological…

Nuclear Theory · Physics 2022-12-28 Wouter Ryssens , Guillaume Scamps , S. Goriely , Michael Bender

Uncertainties in nuclear models have a major impact on simulations that aim at understanding the origin of heavy elements in the universe through the rapid neutron capture process ($r$ process) of nucleosynthesis. Within the framework of…

Nuclear Theory · Physics 2020-05-20 T. M. Sprouse , R. Navarro Perez , R. Surman , M. R. Mumpower , G. C. McLaughlin , N. Schunck

Theoretical predictions of element yields from the rapid neutron capture (r-) process are subject to large uncertainties due to incomplete knowledge of nuclear properties and approximative hydrodynamical modeling of matter ejection. A major…

High Energy Astrophysical Phenomena · Physics 2025-02-12 S. Martinet , S. Goriely

Self-consistent mean field (MF) and beyond-mean-field (BMF) calculations of masses, separation energies and $2^{+}_{1}$ excitation energies of even-even nuclei where experimental data is available are presented. The functionals used are…

Nuclear Theory · Physics 2015-04-21 Tomás R. Rodríguez , Alexander Arzhanov , Gabriel Martínez-Pinedo

Nuclear masses are the most fundamental of all nuclear properties, yet they can provide a wealth of knowledge, including information on astrophysical sites, constraints on existing theory, and fundamental symmetries. In nearly all…

Nuclear Experiment · Physics 2019-06-14 Michael A. Famiano

Analyzing global data on the EMC effect, which denotes differences in parton distribution functions in nuclei compared to unbound nucleons, reveals tensions. Precise measurements at Jefferson Lab, studying both x and A dependence, show…

Nuclear Experiment · Physics 2024-02-28 S. Moran , M. Arratia , J. Arrington , D. Gaskell , B. Schmookler

The Lagrangian density of standard relativistic mean-field (RMF) models with density-dependent meson-nucleon coupling vertices is modified by introducing couplings of the meson fields to derivative nucleon densities. As a consequence, the…

Nuclear Theory · Physics 2007-05-23 S. Typel

We derive stability estimates for three commonly used radial basis function (RBF) methods to solve hyperbolic time-dependent PDEs: the RBF generated finite difference (RBF-FD) method, the RBF partition of unity method (RBF-PUM) and Kansa's…

Numerical Analysis · Mathematics 2024-08-27 Igor Tominec , Murtazo Nazarov , Elisabeth Larsson

The ground state correlation energies associated with collective surface and pairing vibrations are calculated for Pb- and Ca-isotopes. It is shown that this contribution, when added to those predicted by one of the most accurate modern…

Nuclear Theory · Physics 2009-11-10 S. Baroni , M. Armati , F. Barranco , R. A. Broglia , G. Colo' , G. Gori , E. Vigezzi

The majority of nuclear reactions in astrophysics involve unstable nuclei which are not fully accessible by experiments yet. Therefore, there is high demand for reliable predictions of cross sections and reaction rates by theoretical means.…

Astrophysics · Physics 2010-12-13 T. Rauscher , R. D. Hoffman , S. E. Woosley , F. -K. Thielemann

In this paper, the accuracy of two mesh-free approximation approaches, the Gravity model and Radial Basis Function, are compared. The two schemes' convergence behaviors prove that RBF is faster and more accurate than the Gravity model. As a…

Machine Learning · Computer Science 2021-03-23 Amirehsan Ghasemi , Kelvin J Msechu , Arash Ghasemi , Mbakisya A. Onyango , Ignatius Fomunung , Joseph Owino

Machine learning methods and uncertainty quantification have been gaining interest throughout the last several years in low-energy nuclear physics. In particular, Gaussian processes and Bayesian Neural Networks have increasingly been…

Nuclear Theory · Physics 2022-07-27 A. E. Lovell , A. T. Mohan , T. M. Sprouse , M. R. Mumpower

This study investigates the application of deep learning models-recurrent neural networks, gated recurrent units, and long short-term memory networks-for predicting nuclear binding energies. Utilizing data from the Atomic Mass Evaluation…

Nuclear Theory · Physics 2025-03-26 Amir Jalili , Feng Pan , Ai Xi Chen , Jerry P. Draayer

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…

Nuclear Theory · Physics 2009-11-10 P. Lava , M. C. Martinez , J. Ryckebusch , J. A. Caballero , J. M. Udias

The nuclear charge density distribution plays an important role in nuclear physics and atomic physics. As one of the most frequently used models to obtain charge density distribution, the two-parameter fermi (2pF) model has been widely…

Nuclear Theory · Physics 2024-04-17 Tian-Shuai Shang , Jian Li , Zhong-Ming Niu

Accurate estimation of nuclear masses and their prediction beyond the experimentally explored domains of the nuclear landscape are crucial to an understanding of the fundamental origin of nuclear properties and to many applications of…

Nuclear Theory · Physics 2023-05-09 Babette Dellen , Uwe Jaekel , Paulo S. A. Freitas , John W. Clark

While pseudospectral (PS) methods can feature very high accuracy, they tend to be severely limited in terms of geometric flexibility. Application of global radial basis functions overcomes this, however at the expense of problematic…

Numerical Analysis · Mathematics 2017-05-09 Pankaj K Mishra , Sankar K Nath , Gregor Kosec , Mrinal K Sen

We introduce and investigate matrix approximation by decomposition into a sum of radial basis function (RBF) components. An RBF component is a generalization of the outer product between a pair of vectors, where an RBF function replaces the…

Machine Learning · Computer Science 2021-06-25 Elizaveta Rebrova , Yu-Hang Tang

We show that the charge radii of neighboring atomic nuclei, independent of atomic number and charge, follow remarkably very simple relations, despite the fact that atomic nuclei are complex finite many-body systems governed by the laws of…

Nuclear Theory · Physics 2014-11-25 B. H. Sun , Y. Lu , J. P. Peng , C. Y. Liu , Y. M. Zhao

We develop a nuclear mass model that is based on chiral effective field theory at next-to-next-to leading order. Nuclear binding energies are computed via the Hartree-Fock method using a Hamiltonian from delta-full chiral effective field…

Nuclear Theory · Physics 2025-04-30 C. Mishra , A. Ekström , G. Hagen , M. Menickelly , T. Papenbrock , S. M. Wild
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