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Related papers: Inverse Kohn-Sham Density Functional Theory: Progr…

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The Ryabinkin-Kohut-Staroverov (RKS) and Kanungo-Zimmerman-Gavini (KZG) methods offer two approaches to find exchange-correlation (XC) potentials from ground state densities. The RKS method utilizes the one- and two-particle reduced density…

Chemical Physics · Physics 2024-08-06 Bikash Kanungo , Soumi Tribedi , Paul M. Zimmerman , Vikram Gavini

We reexamine the recently introduced basis-set correction theory based on density-functional theory consisting in correcting the basis-set incompleteness error of wave-function methods using a density functional. We use a one-dimensional…

Chemical Physics · Physics 2022-02-16 Diata Traore , Emmanuel Giner , Julien Toulouse

Kohn-Sham (KS) density functional theory (DFT) is a very efficient method for calculating various properties of solids as, for instance, the total energy, the electron density, or the electronic band structure. The KS-DFT method leads to…

Materials Science · Physics 2019-09-20 Fabien Tran , Jan Doumont , Leila Kalantari , Ahmad W. Huran , Miguel A. L. Marques , Peter Blaha

We introduce a general, variational scheme applied to Kohn-Sham density functional theory that allows for partitioning of the ground-state density matrix into distinct spectral domains, each of which spanned by an independent diagonal…

Plasma Physics · Physics 2023-08-29 Babak Sadigh , Daniel Aberg , John Pask

We present an implementation of the optimised effective potential (OEP) scheme for the exact-exchange (EXX) and random phase approximation (RPA) energy functionals and apply these methods to a range of bulk materials. We calculate the…

Materials Science · Physics 2014-05-16 Jiří Klimeš , Georg Kresse

We present a rigorous formulation of generalized Kohn-Sham density-functional theory. This provides a straightforward Kohn-Sham description of many-body systems based not only on particle-density but also on any other observable. We…

Strongly Correlated Electrons · Physics 2008-02-03 M. Valiev , G. W. Fernando

As density functional theory conventionally assumes that the density of a chosen model system (e.g., the Kohn-Sham system) is the same as the exact one, one might expect that approximations to the exact density introduce supplementary…

Chemical Physics · Physics 2009-02-17 A. Savin

A novel algorithm was recently presented to utilize emerging time dependent probability density data to extract molecular potential energy surfaces. This paper builds on the previous work and seeks to enhance the capabilities of the…

Chemical Physics · Physics 2009-11-07 Lukas Kurtz , Herschel Rabitz , Regina de Vivie-Riedle

Frozen Density Embedding (FDE) represents a versatile embedding scheme to describe the environmental effect on the electron dynamics in molecular systems. The extension of the general theory of FDE to the real-time time-dependent Kohn-Sham…

The interaction between the foundation structures and the soil has been developed for many engineering applications. For the determination of the stress in foundation structure it is needed to determine the influence of the stiffness of…

Numerical Analysis · Mathematics 2022-05-17 Leonardo Scandurra

In this work we give a comprehensive derivation of an exact and numerically feasible method to perform ab-initio calculations of quantum particles interacting with a quantized electromagnetic field. We present a hierachy of…

The gas of the interacted electrons is usually described within Kohn-Sham approximation by the set of Poisson and Schr\"{o}dinger equations with an effective potential for the single-particle wave functions. The solution of these equations…

Materials Science · Physics 2007-05-23 A. Ya. Shul'man , D. V. Posvyanskii

We address the inverse problem of cosmic large-scale structure reconstruction from a Bayesian perspective. For a linear data model, a number of known and novel reconstruction schemes, which differ in terms of the underlying signal prior,…

Astrophysics · Physics 2009-11-06 F. S. Kitaura , T. A. Ensslin

A system of electrons in a local or nonlocal external potential can be studied with 1-matrix functional theory (1MFT), which is similar to density functional theory (DFT) but takes the one-particle reduced density matrix (1-matrix) instead…

Strongly Correlated Electrons · Physics 2008-07-23 Ryan Requist , Oleg Pankratov

This work further develops the calculation of QED effects in a finite Gaussian basis. We focus on the non-linear ${\alpha}(Z{\alpha})^{n\ge 3}$ contribution to the vacuum polarization density, computing the energy shift of 1s$_{1/2}$ states…

Quantum Physics · Physics 2025-12-19 Ryan Benazzouk , Maen Salman , Trond Saue

Calculations in Kohn-Sham density functional theory crucially rely on high-quality approximations for the exchange-correlation (xc) functional. Standard local and semi-local approximations fail to predict the ionization potential (IP) and…

Materials Science · Physics 2023-05-03 Sharon Lavie , Yuli Goshen , Eli Kraisler

Recently, a new connection between density functional theory and kinetic theory has been proposed. In particular, it was shown that the Kohn-Sham (KS) equations can be reformulated as a macroscopic limit of the steady-state solution of a…

Chemical Physics · Physics 2015-10-28 M. Mendoza , H. J. Herrmann , S. Succi

An atom placed inside a cavity of finite dimension offers many interesting features, and thus has been a topic of great current activity. This work proposes a density functional approach to pursue both ground and excited states of a…

Quantum Physics · Physics 2022-05-20 Sangita Majumdar , Amlan K. Roy

The standard way to calculate the Kohn-Sham orbitals utilizes an approximation of the potential. The approximation consists in a projection of the potential into a finite subspace of basis functions. The orbitals, calculated with the…

Computational Physics · Physics 2018-11-19 Rudolf Zeller

This work aims at solving the problems with intractable sparsity-inducing norms that are often encountered in various machine learning tasks, such as multi-task learning, subspace clustering, feature selection, robust principal component…

Machine Learning · Computer Science 2019-07-03 Feiping Nie , Zhanxuan Hu , Xiaoqian Wang , Rong Wang , Xuelong Li , Heng Huang