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Chemical accuracy serves as an important metric for assessing the effectiveness of the numerical method in Kohn--Sham density functional theory. It is found that to achieve chemical accuracy, not only the Kohn--Sham wavefunctions but also…

Computational Physics · Physics 2023-10-25 Yang Kuang , Yedan Shen , Guanghui Hu

The frozen spin method can be effectively used for a high-precision measurement of the tensor electric and magnetic polarizabilities of the deuteron and other nuclei in storage rings. For the deuteron, this method would provide the…

Nuclear Theory · Physics 2009-10-29 Alexander J. Silenko

Background: Fission modes are typically characterised by fragment mass and total kinetic energy centroids, around which a distribution of these variables is observed. These distributions are usually fitted with Gaussian functions. Purpose:…

Nuclear Theory · Physics 2025-03-24 Patrick McGlynn , Cedric Simenel

Locality of compact one-electron orbitals expanded strictly in terms of local subsets of basis functions can be exploited in density functional theory (DFT) to achieve linear growth of computation time with systems size, crucial in…

Computational Physics · Physics 2021-10-01 Yifei Shi , Jessica Karaguesian , Rustam Z. Khaliullin

Density functional theory (DFT) embedding provides a formally exact framework for interfacing correlated wave-function theory (WFT) methods with lower-level descriptions of electronic structure. Here, we report techniques to improve the…

Chemical Physics · Physics 2015-06-12 Jason D. Goodpaster , Taylor A. Barnes , Frederick R. Manby , Thomas F. Miller

A collection of algorithms is described for numerically computing with smooth functions defined on the unit disk. Low rank approximations to functions in polar geometries are formed by synthesizing the disk analogue of the double Fourier…

Numerical Analysis · Mathematics 2017-03-28 Heather Wilber , Alex Townsend , Grady Wright

We investigate asymmetric nuclear matter with two- and three-nucleon interactions based on chiral effective field theory, where three-body forces are fit only to light nuclei. Focusing on neutron-rich matter, we calculate the energy for…

Nuclear Theory · Physics 2015-06-17 C. Drischler , V. Soma , A. Schwenk

A set of bi-orthogonal potential-density basis functions is introduced to model the density and its associated gravitational field of three dimensional stellar systems. Radial components of our basis functions are weighted integral forms of…

Astrophysics · Physics 2009-11-13 Alireza Rahmati , Mir Abbas Jalali

In this study, Physics-Informed Neural Networks (PINNs) are skilfully applied to explore a diverse range of pulsar magneto-spheric models, specifically focusing on axisymmetric cases. The study successfully reproduced various axisymmetric…

High Energy Astrophysical Phenomena · Physics 2023-10-11 Petros Stefanou , Jorge F. Urbán , José A. Pons

We present a numerical method for solving the Poisson equation on a nested grid. The nested grid consists of uniform grids having different grid spacing and is designed to cover the space closer to the center with a finer grid. Thus our…

Astrophysics · Physics 2009-11-07 Tomoaki Matsumoto , Tomoyuki Hanawa

The marriage of density functional theory (DFT) and deep learning methods has the potential to revolutionize modern computational materials science. Here we develop a deep neural network approach to represent DFT Hamiltonian (DeepH) of…

Materials Science · Physics 2023-01-02 He Li , Zun Wang , Nianlong Zou , Meng Ye , Runzhang Xu , Xiaoxun Gong , Wenhui Duan , Yong Xu

Computing gravity field of a mass body is a core routine to image anomalous density structures in the Earth. In this study, we report the existence of analytical routines to accurately compute the gravity potential and gravity field of a…

An empirical formula for a Shu distribution function that reproduces a thin disc with exponential surface density to good accuracy is presented. The formula has two free parameters that specify the functional form of the velocity…

Astrophysics of Galaxies · Physics 2015-06-16 Sanjib Sharma , Joss Bland-Hawthorn

We present a new method for generating the gravitational field of thin disks within the Weyl class of static and axially symmetric spacetimes. Such a gravitational field is described by two metric functions: one satisfies the Laplace…

General Relativity and Quantum Cosmology · Physics 2023-10-27 David Kofroň , Petr Kotlařík , Oldřich Semerák

In the framework of chiral perturbation theory we demonstrate the equivalence of the supersymmetric and the replica methods in the symmetry breaking classes of Dyson indices \beta=1 and \beta=4. Schwinger-Dyson equations are used to derive…

High Energy Physics - Theory · Physics 2009-11-10 Jesper Levinsen

We explore the connection between fractional order partial differential equations in two or more spatial dimensions with boundary integral operators to develop techniques that enable one to efficiently tackle the integral fractional…

Numerical Analysis · Mathematics 2019-05-27 Mark Ainsworth , Christian Glusa

Hybrid density functional theory (DFT) remains intractable for large periodic systems due to the demanding computational cost of exact exchange. We apply the tensor hypercontraction (THC) (or interpolative separable density fitting)…

Computational Physics · Physics 2023-10-13 Adam Rettig , Joonho Lee , Martin Head-Gordon

We present a real-space formulation for coarse-graining Kohn-Sham Density Functional Theory that significantly speeds up the analysis of material defects without appreciable loss of accuracy. The approximation scheme consists of two steps.…

Computational Physics · Physics 2015-06-11 Phanish Suryanarayana , Kaushik Bhattacharya , Michael Ortiz

Partition density functional theory is a formally exact procedure for calculating molecular properties from Kohn-Sham calculations on isolated fragments, interacting via a global partition potential that is a functional of the fragment…

Other Condensed Matter · Physics 2015-05-13 Peter Elliott , Kieron Burke , Morrel H. Cohen , Adam Wasserman

Approximation using Fourier features is a popular technique for scaling kernel methods to large-scale problems, with myriad applications in machine learning and statistics. This method replaces the integral representation of a…

Machine Learning · Statistics 2024-08-26 Ayoub Belhadji , Qianyu Julie Zhu , Youssef Marzouk