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Machine learning interatomic potentials (MLIPs) based on a large dataset obtained by density functional theory (DFT) calculation have been developed recently. This study gives both conceptual and practical bases for the high accuracy of…

Materials Science · Physics 2017-11-08 Akira Takahashi , Atsuto Seko , Isao Tanaka

\gamma-softness in atomic nuclei is investigated in the framework of energy density functionals. By mapping constrained microscopic energy surfaces for a set of representative non-axial medium-heavy and heavy nuclei to a Hamiltonian of the…

Nuclear Theory · Physics 2015-05-30 K. Nomura , N. Shimizu , D. Vretenar , T. Niksic , T. Otsuka

Spectral functions of the nucleon and its negative parity excited state in nuclear matter are studied using QCD sum rules and the maximum entropy method (MEM). It is found that in-medium modifications of the spectral functions are…

High Energy Physics - Phenomenology · Physics 2016-10-14 Keisuke Ohtani , Philipp Gubler , Makoto Oka

Background: Saturation of nuclear density is a fundamental property of atomic nuclei but in reality, the nuclear internal density distribution is not uniform, e.g., some nuclei are known to have the so-called bubble structure, in which the…

Nuclear Theory · Physics 2025-01-10 Shuichiro Ebata , Wataru Horiuchi

Empirically determined values of the nuclear volume and surface symmetry energy coefficients from nuclear masses are expressed in terms of density distributions of nucleons in heavy nuclei in the local density approximation. This is then…

Nuclear Theory · Physics 2015-06-16 B. K. Agrawal , J. N. De , S. K. Samaddar , G. Colo , A. Sulaksono

Dipole bosons are introduced in the interacting boson model (IBM) by means of the self-consistent mean-field method. The constrained mean-field calculations employing a given nuclear energy density functional yield the potential energy…

Nuclear Theory · Physics 2025-10-21 K. Nomura

This study investigates different Scientific Machine Learning (SciML) approaches for the analysis of functionally graded (FG) porous beams and compares them under a new framework. The beam material properties are assumed to vary as an…

Machine Learning · Computer Science 2024-12-25 Mohammad Sadegh Eshaghi , Mostafa Bamdad , Cosmin Anitescu , Yizheng Wang , Xiaoying Zhuang , Timon Rabczuk

A microscopic framework of nuclear energy density functionals is reviewed, which establishes a direct relation between low-energy QCD and nuclear structure, synthesizing effective field theory methods and principles of density functional…

Nuclear Theory · Physics 2008-11-26 Dario Vretenar

Five effects of correction of the asymptotic potential error in density functionals are identified that significantly improve calculated properties of molecular excited states involving charge-transfer character. Newly developed…

Materials Science · Physics 2022-02-04 Musen Li , Rika Kobayashi , Roger D. Amos , Michael J. Ford , Jeffrey R. Reimers

Scattering-type scanning near-field optical microscopy (s-SNOM) is a powerful technique for extreme subwavelength imaging and spectroscopy, with around 20 nm spatial resolution. But quantitative relationships between experiment and material…

In the framework of the relativistic mean field model with Thomas-Fermi approximation, we study the structures of low density nuclear matter in a three-dimensional geometry with reflection symmetry. The numerical accuracy and efficiency are…

[Background] Symmetry restoration and configuration mixing in the spirit of the generator coordinate method based on energy density functionals have become widely used techniques in low-energy nuclear structure physics. Recently, it has…

Nuclear Theory · Physics 2012-11-27 K. Washiyama , K. Bennaceur , B. Avez , M. Bender , P. -H. Heenen , V. Hellemans

We present an evaluation of the non-mesonic decay widths for Lambda-hypernuclei (Lambda N --> NN, Lambda NN --> NNN) within the framework of the polarization propagator method. The full Lambda self-energy is evaluated microscopically in…

Nuclear Theory · Physics 2009-10-31 W. M. Alberico , A. De Pace , G. Garbarino , R. Cenni

We use quantum Monte Carlo methods in the framework of the interacting nuclear shell model to calculate the statistical properties of nuclei at finite temperature and/or excitation energies. With this approach we can carry out realistic…

Nuclear Theory · Physics 2009-11-11 Y. Alhassid

This work introduces a comprehensive approach to assess the sensitivity of model outputs to changes in parameter values, constrained by the combination of prior beliefs and data. This novel approach identifies stiff parameter combinations…

A new alternative approach to calculate the ratio of the surface to volume components of the nuclear symmetry energy is proposed in the framework of the coherent density fluctuation model (CDFM). A new expression (scheme II) for the ratio…

The development of a modern and more realistic nuclear energy density functional (EDF) for accurate predictions of properties of nuclei is the subject of enhanced activity, since it is very important for the study of properties of nuclear…

Nuclear Theory · Physics 2019-11-14 S. Shlomo , A. I. Sanzhur

Nuclear symmetry energy $E_{\rm{sym}}(\rho)$ at density $\rho$ is normally expanded or simply parameterized as a function of $\chi=(\rho-\rho_0)/3\rho_0$ in the form of $E_{\rm{sym}}(\rho)\approx…

Nuclear Theory · Physics 2021-05-26 Bao-Jun Cai , Bao-An Li

Nuclear density functional theory (DFT) is the only microscopic, global approach to the structure of atomic nuclei. It is used in numerous applications, from determining the limits of stability to gaining a deep understanding of the…

Nuclear Theory · Physics 2015-02-06 Nicolas Schunck , Jordan D. McDonnell , Jason Sarich , Stefan M. Wild , Dave Higdon

In this article, we study approximation properties of the variation spaces corresponding to shallow neural networks with a variety of activation functions. We introduce two main tools for estimating the metric entropy, approximation rates,…

Machine Learning · Statistics 2024-02-26 Jonathan W. Siegel , Jinchao Xu
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