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We describe how to apply the recently developed pole expansion and selected inversion (PEXSI) technique to Kohn-Sham density function theory (DFT) electronic structure calculations that are based on atomic orbital discretization. We give…

Computational Physics · Physics 2015-06-04 Lin Lin , Mohan Chen , Chao Yang , Lixin He

Quantum mechanical calculations for material modelling using Kohn-Sham density functional theory (DFT) involve the solution of a nonlinear eigenvalue problem for $N$ smallest eigenvector-eigenvalue pairs with $N$ proportional to the number…

Computational Physics · Physics 2023-09-26 Sameer Khadatkar , Phani Motamarri

Effective field theory (EFT) methods are applied to density functional theory (DFT) as part of a program to systematically go beyond mean-field approaches to medium and heavy nuclei. A system of fermions with short-range, natural…

Nuclear Theory · Physics 2007-05-23 S. J. Puglia , A. Bhattacharyya , R. J. Furnstahl

The nuclear energy density functional method at finite temperature is a useful tool for studies of nuclear structure at high excitation, and also for researches of nuclear matter involved in explosive stellar phenomena and neutron stars.…

Nuclear Theory · Physics 2023-03-02 Takashi Nakatsukasa

The practical success of density functional theory (DFT) is largely credited to the Kohn-Sham approach, which enables the exact calculation of the non-interacting electron kinetic energy via an auxiliary noninteracting system. Yet, the…

Computational Physics · Physics 2025-03-21 Sangita Majumdar , Zekun Shi , Giovanni Vignale

We showcase the advantages of orbital-free density-potential functional theory (DPFT), a more flexible variant of Hohenberg-Kohn density functional theory. DPFT resolves the usual trouble with the gradient-expanded kinetic energy functional…

Quantum Gases · Physics 2021-06-16 Martin-Isbjörn Trappe , Jun Hao Hue , Berthold-Georg Englert

We present a spectrum-splitting approach to conduct all-electron Kohn-Sham density functional theory (DFT) calculations by employing Fermi-operator expansion of the Kohn-Sham Hamiltonian. The proposed approach splits the subspace containing…

Computational Physics · Physics 2017-02-01 Phani Motamarri , Vikram Gavini , Kaushik Bhattacharya , Michael Ortiz

In this paper we will present some alternative types of discretization methods (discrete approximation) for the fractional-order (FO) differentiator and their application to the FO dynamical system described by the FO differential equation…

Optimization and Control · Mathematics 2007-05-23 L. Dorcak , I. Petras , J. Terpak , M. Zborovjan

Density functional theory (DFT) and beyond-DFT methods are often used in combination with photoelectron spectroscopy to obtain physical insights into the electronic structure of molecules and solids. The Kohn-Sham eigenvalues are not…

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

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

Effective field theory (EFT) methods for a uniform system of fermions with short-range, natural interactions are extended to include pairing correlations, as part of a program to develop a systematic Kohn-Sham density functional theory…

Nuclear Theory · Physics 2008-11-26 R. J. Furnstahl , H. -W. Hammer , S. J. Puglia

The inverse problem of Kohn-Sham density functional theory (DFT) is often solved in an effort to benchmark and design approximate exchange-correlation potentials. The forward and inverse problems of DFT rely on the same equations but the…

Chemical Physics · Physics 2017-08-02 Daniel Jensen , Adam Wasserman

We present an accurate, efficient and massively parallel finite-element code, DFT-FE, for large-scale ab-initio calculations (reaching $\sim 100,000$ electrons) using Kohn-Sham density functional theory (DFT). DFT-FE is based on a local…

Computational Physics · Physics 2020-01-08 Phani Motamarri , Sambit Das , Shiva Rudraraju , Krishnendu Ghosh , Denis Davydov , Vikram Gavini

Here we present a density matrix based KS inversion method formulated entirely within a Gaussian basis representation to optimize a KS potential matrix that reproduces a target electron density. Inverse Kohn-Sham (KS) density functional…

Chemical Physics · Physics 2026-03-24 Ziwei Chai , Sandra Luber

We describe a scheme for efficient large-scale electronic-structure calculations based on the combination of the pole expansion and selected inversion (PEXSI) technique with the SIESTA method, which uses numerical atomic orbitals within the…

Computational Physics · Physics 2015-06-19 Lin Lin , Alberto García , Georg Huhs , Chao Yang

Computational high-throughput virtual screening is essential for identifying redox-active molecules for sustainable applications such as electrochemical carbon capture. A primary challenge in this approach is the high computational cost…

Chemical Physics · Physics 2026-01-19 Yicheng Chen , Lixue Cheng , Yan Jing , Peichen Zhong

By partitioning the electron density into subsystem contributions, the Frozen Density Embedding (FDE) formulation of subsystem DFT has recently emerged as a powerful tool for reducing the computational scaling of Kohn--Sham DFT. To date,…

Materials Science · Physics 2015-06-22 Alessandro Genova , Davide Ceresoli , Michele Pavanello

We re-adapt a spectral renormalization method, introduced in nonlinear optics, to solve the Kohn-Sham (KS) equations of density functional theory (DFT), with a focus on functionals based on the strictly-correlated electrons (SCE) regime,…

Strongly Correlated Electrons · Physics 2020-04-23 Juri Grossi , Ziad H. Musslimani , Michael Seidl , Paola Gori-Giorgi

This paper is concerned with sequential filtering based stochastic optimization (FSO) approaches that leverage a probabilistic perspective to implement the incremental proximity method (IPM). The present FSO methods are derived based on the…

Machine Learning · Computer Science 2020-01-08 Bin Liu
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