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Deep learning electronic structures from ab initio calculations holds great potential to revolutionize computational materials studies. While existing methods proved success in deep-learning density functional theory (DFT) Hamiltonian…

Density Functional Theory (DFT) is one of the most widely used methods for "ab initio" calculations of the structure of atoms, molecules, crystals, surfaces, and their interactions. Unfortunately, the customary introduction to DFT is often…

Physics Education · Physics 2010-12-07 Nathan Argaman , Guy Makov

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

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

Modern density functional approximations achieve moderate accuracy at low computational cost for many electronic structure calculations. Some background is given relating the gradient expansion of density functional theory to the WKB…

Chemical Physics · Physics 2021-01-27 Kieron Burke

Quantum Chemistry and Physics have been pinpointed as killer applications for quantum computers, and quantum algorithms have been designed to solve the Schr\"odinger equation with the wavefunction formalism. It is yet limited to small…

Quantum Physics · Physics 2023-03-29 Bruno Senjean , Saad Yalouz , Matthieu Saubanère

Linear scaling density functional theory approaches to electronic structure are often based on the tendency of electrons to localize even in large atomic and molecular systems. However, in many cases of actual interest, for example in…

Chemical Physics · Physics 2022-03-25 Marcel David Fabian , Ben Shpiro , Roi Baer

The fractional quantum Hall effect remains a captivating area in condensed matter physics, characterized by strongly correlated topological order, which manifests as fractionalized excitations and anyonic statistics. Numerical simulations,…

Strongly Correlated Electrons · Physics 2025-10-27 Yi Yang , Yayun Hu , Zi-Xiang Hu

To go beyond Gaussian approximation to the Hohenberg-Kohn free energy playing the key role in the density functional theory (DFT), the density functional \textit{integral} representation would be relevant, because field theoretical approach…

Soft Condensed Matter · Physics 2009-10-31 H. Frusawa , R. Hayakawa

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 advent of the Hohenberg-Kohn theorem in 1964, its extension to finite-T, Kohn-Sham theory, and relativistic extensions provide the well-established formalism of density-functional theory (DFT). This theory enables the calculation of all…

Quantum Physics · Physics 2013-07-18 M. W. C. Dharma-wardana

Density functional theory (DFT) has become the most popular approach to electronic structure across disciplines, especially in material and chemical sciences. Last year, at least 30,000 papers used DFT to make useful predictions or give…

Chemical Physics · Physics 2017-01-05 Justin C. Smith , Francisca Sagredo , Kieron Burke

Recently, sophisticated deep learning-based approaches have been developed for generating efficient initial guesses to accelerate the convergence of density functional theory (DFT) calculations. While the actual initial guesses are often…

Chemical Physics · Physics 2026-03-24 Zhe Liu , Yuyan Ni , Zhichen Pu , Qiming Sun , Siyuan Liu , Wen Yan

We argue that the success of DFT can be understood in terms of a semiclassical expansion around a very specific limit. This limit was identified long ago by Lieb and Simon for the total electronic energy of a system. This is a universal…

Chemical Physics · Physics 2021-05-18 Pavel Okun , Kieron Burke

The fabrication, utilisation, and efficiency of quantum technologies rely on a good understanding of quantum thermodynamic properties. Many-body systems are often used as hardware for these quantum devices, but interactions between…

Strongly Correlated Electrons · Physics 2022-04-26 Krissia Zawadzki , Amy Skelt , Irene D'Amico

Density functional theory (DFT), the most widely adopted method in modern computational chemistry, fails to describe accurately the electronic structure of strongly correlated systems. Here we show that DFT can be formally and practically…

Chemical Physics · Physics 2022-04-18 Daniel Gibney , Jan-Niklas Boyn , David A. Mazziotti

Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion (ICF) applications. The work horse of warm dense…

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…

Due to efficient scaling with electron number N, density functional theory (DFT) is widely used for studies of large molecules and solids. Restriction of an exact mean-field theory to local potential functions has recently been questioned.…

Other Condensed Matter · Physics 2015-06-24 Robert K. Nesbet

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