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The accuracy of density-functional theory (DFT) is determined by the quality of the approximate functionals, such as exchange-correlation in electronic DFT and the excess functional in the classical DFT formalism of fluids. The exact…

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

Constrained density functional theory (cDFT) is a versatile electronic structure method that enables ground-state calculations to be performed subject to physical constraints. It thereby broadens their applicability and utility. Automated…

Other Condensed Matter · Physics 2016-08-03 David D. O'Regan , Gilberto Teobaldi

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

We propose a new molecular simulation framework that combines the transferability, robustness and chemical flexibility of an ab initio method with the accuracy and efficiency of a machine learned force field. The key to achieve this mix is…

Computational Physics · Physics 2020-01-08 Sebastian Dick , Marivi Fernandez-Serra

Density functional theory (DFT) has transformed our ability to investigate and understand electronic ground states. In its original formulation, however, DFT is not suited to addressing (e.g.) degenerate ground states, mixed states with…

Chemical Physics · Physics 2025-10-30 Tim Gould , Leeor Kronik , Stefano Pittalis

Development of the electronic kinetic-energy density functional is a subject of major interest in theoretical physics and chemistry. In this work, the nonlocal kinetic-energy functional is developed in terms of the response function for the…

Chemical Physics · Physics 2022-06-17 Hideaki Takahashi

Density functional theory (DFT) is routinely employed in material science and in quantum chemistry to simulate weakly correlated electronic systems. Recently, deep learning (DL) techniques have been adopted to develop promising functionals…

Strongly Correlated Electrons · Physics 2023-10-02 Emanuele Costa , Rosario Fazio , Sebastiano Pilati

With the growth of computational resources, the scope of electronic structure simulations has increased greatly. Artificial intelligence and robust data analysis hold the promise to accelerate large-scale simulations and their analysis to…

Materials Science · Physics 2023-07-27 Lenz Fiedler , Karan Shah , Michael Bussmann , Attila Cangi

Self-consistent-field (SCF) approximations formulated using Hartree-Fock (HF) or Kohn-Sham Density Functional Theory (KS-DFT) both have the potential to yield multiple solutions. However, the formal relationship between multiple solutions…

Chemical Physics · Physics 2021-01-06 Rhiannon A. Zarotiadis , Hugh G. A. Burton , Alex J. W. Thom

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 compare two different approaches to investigations of many-electron systems. The first is the Hartree-Fock (HF) method and the second is the Density Functional Theory (DFT). Overview of the main features and peculiar properties of the HF…

Materials Science · Physics 2009-11-07 M. Ya. Amusia , A. Z. Msezane , V. R. Shaginyan

Orbital-free Density Functional Theory (OF-DFT) has been used when studying atoms, molecules and solids. In nuclear physics, there has been basically no application of OF-DFT so far, as the Density Functional Theory (DFT) has been widely…

Nuclear Theory · Physics 2023-08-03 Gianluca Colo' , Kouichi Hagino

We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of thirteen electronic ground-state properties of organic molecules. The performance of each…

Computational screening has become a powerful complement to experimental efforts in the discovery of high-performance photovoltaic (PV) materials. Most workflows rely on density functional theory (DFT) to estimate electronic and optical…

Materials Science · Physics 2025-07-18 Matthew Walker , Keith T. Butler

We propose a novel scheme to bring reduced density matrix functional theory (RDMFT) into the realm of density functional theory (DFT) that preserves the accurate density functional description at equilibrium, while incorporating accurately…

Chemical Physics · Physics 2014-11-07 Nektarios N. Lathiotakis , Nicole Helbig , Angel Rubio , Nikitas I. Gidopoulos

A quantitative and predictive theory of quantum light-matter interactions in ultra thin materials involves several fundamental challenges. Any realistic model must simultaneously account for the ultra-confined plasmonic modes and their…

Density functional theory (DFT) provides convenient electronic structure methods for the study of molecular systems and materials. Regular Kohn-Sham DFT calculations rely on unitary transformations to determine the ground-state electronic…

Chemical Physics · Physics 2022-10-10 Greta Jacobson , Juan M. Marmolejo-Tejada , Martín A. Mosquera

Density Functional Theory (DFT) has become the quasi-standard for ab-initio simulations for a wide range of applications. While the intrinsic cubic scaling of DFT was for a long time limiting the accessible system size to some hundred…

Materials Science · Physics 2018-02-23 Stephan Mohr , Marc Eixarch , Maximilian Amsler , Mervi J. Mantsinen , Luigi Genovese

Performing density functional theory (DFT) calculations requires a careful choice of computational parameters to ensure convergence and obtain meaningful results. This represents a particularly important problem for high-throughput and…