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Related papers: Kohn-Sham accuracy from orbital-free density funct…

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This work presents a theory to unify the two independent theoretical frameworks of Kohn-Sham (KS) density functional theory (DFT) and reduced density matrix functional theory (RDMFT). The generalization of the KS orbitals to hypercomplex…

Chemical Physics · Physics 2021-11-18 Neil Qiang Su

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

The kinetic energy (KE) kernel, which is defined as the second order functional derivative of the KE functional with respect to density, is the key ingredient to the construction of KE models for orbital free density functional theory…

Materials Science · Physics 2025-05-15 Zhandos A. Moldabekov , Xuecheng Shao , Michele Pavanello , Jan Vorberger , Tobias Dornheim

Adopting an accurate kinetic energy density functional (KEDF) to characterize the noninteracting kinetic energy within the framework of orbital-free density functional theory (OFDFT) is challenging. We propose a new form of the non-local…

Computational Physics · Physics 2024-11-15 Liang Sun , Yuanbo Li , Mohan Chen

By inverting the time-dependent Kohn-Sham equation for a numerically exact dynamics of the helium atom, we show that the dynamical step and peak features of the exact correlation potential found previously in one-dimensional models persist…

Chemical Physics · Physics 2022-07-28 Davood Dar , Lionel Lacombe , Johannes Feist , Neepa Maitra

Modeling many-body quantum systems with strong interactions is one of the core challenges of modern physics. A range of methods has been developed to approach this task, each with its own idiosyncrasies, approximations, and realm of…

Statistical Mechanics · Physics 2018-11-21 Brett Larder , Dirk Gericke , Scott Richardson , Paul Mabey , Thomas White , Gianluca Gregori

We propose a machine learning based approach to develop the exchange-correlation potential of time dependent density functional theory (TDDFT). The neural network projection from the time-varying electron densities to the corresponding…

Computational Physics · Physics 2020-05-20 Yasumitsu Suzuki , Ryo Nagai , Jun Haruyama

We provide {\it a priori} error estimates for the spectral and pseudospectral Fourier (also called planewave) discretizations of the periodic Thomas-Fermi-von Weizs\"acker (TFW) model and of the Kohn-Sham model, within the local density…

Numerical Analysis · Mathematics 2009-09-09 Eric Cancès , Rachida Chakir , Yvon Maday

Orbital-free density functional theory as an extension of traditional Thomas-Fermi theory has attracted a lot of interest in the past decade because of developments in both more accurate kinetic energy functionals and highly efficient…

Materials Science · Physics 2009-11-10 Hong Jiang , Weitao Yang

Quantum mechanical methods based on the density functional theory (DFT) offer a realistic possibility of first-principles design of organic donor-acceptor systems and engineered band-gap materials. This promise is contingent upon the…

Chemical Physics · Physics 2013-12-03 Marcin Modrzejewski , Grzegorz Chałasiński , Małgorzata M. Szczęśniak

Molecular Density Functional Theory (MDFT) offers an efficient implicit- solvent method to estimate molecule solvation free-energies whereas conserving a fully molecular representation of the solvent. Even within a second order ap-…

Soft Condensed Matter · Physics 2014-06-12 Volodymyr P. Sergiievskyi , Guillaume Jeanmairet , Maximilien Levesque , Daniel Borgis

Materials engineering using atomistic modeling is an essential tool for the development of qubits and quantum sensors. Traditional density-functional theory (DFT) does however not adequately capture the complete physics involved, including…

We propose a first-principles time-dependent density functional theoretical (TDDFT) approach in momentum (P) space for quantitative study of electron transport in molecular devices under arbitrary biases. In this approach, the basic…

Mesoscale and Nanoscale Physics · Physics 2009-02-10 Zhongyuan Zhou , Shih-I Chu

We introduce a machine learning (ML) supervised model function that is inspired by the variational principle of physics. This ML hypothesis evolutionary method, termed ML-Omega, allows us to go from data to differential equation(s)…

Chemical Physics · Physics 2024-05-29 Juan I. Rodriguez , Ulises A. Vergara-Beltran

Density Functional Theory (DFT) allows for predicting all the chemical and physical properties of molecular systems from first principles by finding an approximate solution to the many-body Schr\"odinger equation. However, the cost of these…

Machine Learning · Computer Science 2025-06-03 Majdi Hassan , Cristian Gabellini , Hatem Helal , Dominique Beaini , Kirill Neklyudov

Many application models in quantum physics and chemistry require to control multi-electron systems to achieve a desired target configuration. This challenging task appears possible in the framework of time-dependent density functional…

Optimization and Control · Mathematics 2018-03-14 Martin Sprengel , Gabriele Ciaramella , Alfio Borzì

Using principles of asymptotic analysis, we derive the exact leading corrections to the Thomas-Fermi kinetic energy approximation for Kohn-Sham electrons for slabs. This asymptotic expansion approximation includes crucial quantum…

Materials Science · Physics 2024-02-21 Pavel Okun , Antonio C. Cancio , Kieron Burke

We calculate properties like equilibrium lattice parameter, bulk modulus and monovacancy formation energy for nickel (Ni), iron (Fe) and chromium (Cr) using Kohn-Sham density functional theory (DFT). We compare relative performance of local…

Materials Science · Physics 2011-09-15 Prithwish Kumar Nandi , M. C. Valsakumar , Sharat Chandra , H. K. Sahu , C. S. Sundar

The rectangular collocation approach makes it possible to solve the Schr\"odinger equation with basis functions that do not have amplitude in all regions in which wavefunctions have significant amplitude. Collocation points can be…

Computational Physics · Physics 2020-07-01 Jonas Ku , Aditya Kamath , Tucker Carrington , Sergei Manzhos

We propose a general machine learning-based framework for building an accurate and widely-applicable energy functional within the framework of generalized Kohn-Sham density functional theory. To this end, we develop a way of training…

Computational Physics · Physics 2020-12-14 Yixiao Chen , Linfeng Zhang , Han Wang , E Weinan