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Related papers: Density Functional Theory (DFT) for atomic nuclei:…

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A simplified density functional theory (DFT) method for charged adsorbates on an ultrathin, insulating film supported by a metal substrate is developed and presented. This new method is based on a previous DFT development that uses a…

Materials Science · Physics 2017-03-27 Ivan Scivetti , Mats Persson

Incorporating nuclear shell effects within the framework of orbital-free density functional theory (DFT) has remained a longstanding challenge in nuclear physics. While the Hohenberg-Kohn theorem formally guarantees the existence of an…

Nuclear Theory · Physics 2026-03-03 Xinhui Wu , Gianluca Colò , Kouichi Hagino , Pengwei Zhao

Deep neural networks (DNNs) have been used to successfully predict molecular properties calculated based on the Kohn--Sham density functional theory (KS-DFT). Although this prediction is fast and accurate, we believe that a DNN model for…

Chemical Physics · Physics 2020-11-17 Masashi Tsubaki , Teruyasu Mizoguchi

Density Functional Theory (DFT) is a pivotal method within quantum chemistry and materials science, with its core involving the construction and solution of the Kohn-Sham Hamiltonian. Despite its importance, the application of DFT is…

Density functional theory is a successful branch of numerical simulations of quantum systems. While the foundations are rigorously defined, the universal functional must be approximated resulting in a `semi'-ab initio approach. The search…

Quantum Physics · Physics 2017-11-22 James Daniel Whitfield , Norbert Schuch , Frank Verstraete

We use effective field theory to compute the influence of nuclear structure on precision calculations of atomic energy levels. As usual, the EFT's effective couplings correspond to the various nuclear properties (such as the charge radius,…

High Energy Physics - Phenomenology · Physics 2021-05-19 L. Zalavari , C. P. Burgess , P. Hayman , M. Rummel

Time-dependent density-functional theory (TDDFT) is deemed to be a formally rigorous way of dealing with the time-evolution of a many-electron system at the level of electron densities rather than the underlying wavefunctions, which in turn…

Chemical Physics · Physics 2024-11-26 Jochen Schirmer

Partition Density Functional Theory (P-DFT) is a density embedding method that partitions a molecule into fragments by minimizing the sum of fragment energies subject to a local density constraint and a global electron-number constraint. To…

Chemical Physics · Physics 2022-06-29 Kui Zhang , Adam Wasserman

Density functional theory (DFT) has emerged as one of the most versatile and lucrative approaches in electronic structure calculations of many-electron systems in past four decades. Here we give an account of the development of a…

Chemical Physics · Physics 2019-04-19 Abhisek Ghosal , Amlan K. Roy

The classical Density Functional Theory (DFT) is introduced as an application of entropic inference for inhomogeneous fluids at thermal equilibrium. It is shown that entropic inference reproduces the variational principle of DFT when…

Statistical Mechanics · Physics 2021-09-14 Ahmad Yousefi , Ariel Caticha

Density functional theory (DFT) is used in thousands of papers each year, yet lack of universality reduces DFT's predictive capacity, and functionals may produce energy-density imbalances. The absolute electronegativity (\chi) and hardness…

Chemical Physics · Physics 2020-07-15 Klaus A. Moltved , Kasper P. Kepp

New superheavy nuclei are often identified through their characteristic $\alpha$-decay energies, which requires accurate calculations of $Q_{\alpha}$ values. While many $Q_{\alpha}$ predictions are available, little is known about their…

Nuclear Theory · Physics 2019-01-30 Erik Olsen , Witold Nazarewicz

We show that a lattice formulation of density-functional theory (DFT), guided by renormalization-group concepts, can be used to obtain numerical predictions of energy gaps, spin-density profiles, critical exponents, sound velocities,…

Strongly Correlated Electrons · Physics 2009-11-13 Francisco C. Alcaraz , Klaus Capelle

The Hohenberg-Kohn (HK) theorem -- the bedrock of density functional theory (DFT) -- establishes a universal map from the external potential to the energy. It also relates the electron density and atomic forces to the variation of the…

Chemical Physics · Physics 2025-12-15 Sambit Das , Bikash Kanungo , Arghadwip Paul , Vikram Gavini

Recently a novel approach to find approximate exchange-correlation functionals in density-functional theory (DFT) was presented (U. Mordovina et. al., JCTC 15, 5209 (2019)), which relies on approximations to the interacting wave function…

Chemical Physics · Physics 2021-03-04 Iris Theophilou , Teresa E. Reinhard , Angel Rubio , Michael Ruggenthaler

Most realistic calculations of moderately correlated materials begin with a ground-state density functional theory (DFT) calculation. While Kohn-Sham DFT is used in about 40,000 scientific papers each year, the fundamental underpinnings are…

Strongly Correlated Electrons · Physics 2022-09-26 Kieron Burke , John Kozlowski

We review the notion of symmetry breaking and restoration within the frame of nuclear energy density functional methods. We focus on key differences between wave-function- and energy-functional-based methods. In particular, we point to…

Nuclear Theory · Physics 2011-08-17 T. Duguet , J. Sadoudi

This work presents an alternative, general, and in-principle exact extension of electronic Kohn-Sham density functional theory (KS-DFT) to the fully quantum-mechanical molecular problem. Unlike in existing multi-component or…

Chemical Physics · Physics 2024-05-14 Emmanuel Fromager , Benjamin Lasorne

One of the central problems in quantum mechanics is to determine the ground state properties of a system of electrons interacting via the Coulomb potential. Since its introduction by Hohenberg, Kohn, and Sham, Density Functional Theory…

Quantum Physics · Physics 2010-09-28 Norbert Schuch , Frank Verstraete

Combination of deep learning and ab initio calculation has shown great promise in revolutionizing future scientific research, but how to design neural network models incorporating a priori knowledge and symmetry requirements is a key…

Computational Physics · Physics 2023-06-12 Xiaoxun Gong , He Li , Nianlong Zou , Runzhang Xu , Wenhui Duan , Yong Xu
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