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Orbital-free (OF) methods promise significant speed-up of computations based on density functional theory (DFT). In this field, the development of accurate kinetic-energy density functionals remains an open question. In this chapter we…

Materials Science · Physics 2013-05-03 Constantine Yannouleas , Uzi Landman

Density functional theory underlies the most successful and widely used numerical methods for electronic structure prediction of solids. However, it has the fundamental shortcoming that the universal density functional is unknown. In…

Disordered Systems and Neural Networks · Physics 2020-09-23 M. Michael Denner , Mark H. Fischer , Titus Neupert

Density Functional Theory (DFT) is widely used for atomistic simulations. However, its reach stays limited due to several limitations such as lack of accurate exchange-correlation functional, requirement of costly O(N 3) diagonalization…

Quantum Physics · Physics 2026-05-18 Namrata Manglani , Samrit Kumar Maity , Shashank Sharma , Soham Phulare , Sanjay Wandhekar

We present a differentiation framework for plane-wave density-functional theory (DFT) that combines the strengths of forward-mode algorithmic differentiation (AD) and density-functional perturbation theory (DFPT). In the resulting AD-DFPT…

Materials Science · Physics 2025-12-23 Niklas Frederik Schmitz , Bruno Ploumhans , Michael F. Herbst

We introduce a practical hybrid approach that combines orbital-free density functional theory (DFT) with Kohn-Sham DFT for speeding up first-principles molecular dynamics simulations. Equilibrated ionic configurations are generated using…

New energy-density functionals (EDFs) inspired by effective-field theories (EFTs) have been recently proposed. The present work focuses on three of such functionals which were developed to produce satisfactory equations of state for nuclear…

Nuclear Theory · Physics 2018-09-26 Jérémy Bonnard , Marcella Grasso , Denis Lacroix

Multireference density functional theory (MR-DFT) provides a pivotal microscopic framework for the description of the ground state properties, low-lying nuclear spectra and transition properties of atomic nuclei. Conventionally, practical…

Nuclear Theory · Physics 2026-05-05 Xin. Zhang , Kouichi. Hagino

Locality of compact one-electron orbitals expanded strictly in terms of local subsets of basis functions can be exploited in density functional theory (DFT) to achieve linear growth of computation time with systems size, crucial in…

Computational Physics · Physics 2021-10-01 Yifei Shi , Jessica Karaguesian , Rustam Z. Khaliullin

The systematic underestimation of band gaps is one of the most fundamental challenges in semilocal density functional theory (DFT). In addition to hindering the application of DFT to predicting electronic properties, the band gap problem is…

Chemical Physics · Physics 2024-08-27 Kyle Bystrom , Stefano Falletta , Boris Kozinsky

We extend to strongly correlated molecular systems the recently introduced basis-set incompleteness correction based on density-functional theory (DFT) [E. Giner et al., J. Chem. Phys. 149, 194301 (2018)]. This basis-set correction relies…

Chemical Physics · Physics 2020-05-20 Emmanuel Giner , Anthony Scemama , Pierre-François Loos , Julien Toulouse

The present contribution does not aim at replacing the huge and often excellent literature on DFT for atomic nuclei, but tries to provide an updated introduction to this topic. The goal would be, ideally, to help a fresh M.Sc. or Ph.D.…

Nuclear Theory · Physics 2019-08-09 G. Colò

We provide a new formulation of Time-Dependent Density Functional Theory (TDDFT) based on the geometric structure of the set of states constrained to have a fixed density. Orbital-free TDDFT is formulated using a hydrodynamics equation…

For orbital-free {\it ab initio} molecular dynamics, especially on systems in extreme thermodynamic conditions, we provide the first pseudo-potential-adapted generalized gradient approximation (GGA) functional for the non-interacting free…

Chemical Physics · Physics 2020-02-19 Kai Luo , Valentin V. Karasiev , S. B. Trickey

We introduce a novel energy functional for ground-state electronic-structure calculations. Its fundamental variables are the natural spin-orbitals of the implied singlet many-body wave function and their joint occupation probabilities. The…

Chemical Physics · Physics 2015-06-23 Ralph Gebauer , Morrel H. Cohen , Roberto Car

Derivative-Free Optimization (DFO) involves methods that rely solely on evaluations of the objective function. One of the earliest strategies for designing DFO methods is to adapt first-order methods by replacing gradients with…

Optimization and Control · Mathematics 2025-02-12 Timothé Taminiau , Estelle Massart , Geovani Nunes Grapiglia

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

Perdew et al. [Phys. Rev. Lett 49, 1691 (1982)] discovered and proved two different properties of exact Kohn-Sham density functional theory (DFT): (i) The exact total energy versus particle number is a series of linear segments between…

Other Condensed Matter · Physics 2015-03-13 Tamar Stein , Jochen Autschbach , Niranjan Govind , Leeor Kronik , Roi Baer

Classical density functional theory (cDFT) and dynamical density functional theory (DDFT) are modern statistical mechanical theories for modeling many-body colloidal systems at the one-body density level. The theories hinge on knowing the…

Density Functional Theory (DFT) is a robust framework for modeling interacting many-body systems, including the equation of state (EoS) of dense matter. Many models, however, rely on energy functionals based on assumptions that have not…

Nuclear Theory · Physics 2025-06-06 Udita Shukla , Pok Man Lo

Improving the predictive capability of molecular properties in ab initio simulations is essential for advanced material discovery. Despite recent progress making use of machine learning, utilizing deep neural networks to improve quantum…

Chemical Physics · Physics 2021-09-22 Muhammad F. Kasim , Sam M. Vinko