English
Related papers

Related papers: KineticNet: Deep learning a transferable kinetic e…

200 papers

Aspects of Density Functional Resonance Theory (DFRT) [Phys. Rev. Lett. \textbf{107}, 163002 (2011)], a recently developed complex-scaled version of ground-state Density Functional Theory (DFT), are studied in detail. The asymptotic…

Quantum Physics · Physics 2015-06-04 Daniel L. Whitenack , Adam Wasserman

This work continues a program to systematically generalize the Skyrme Hartree-Fock method for medium and heavy nuclei by applying effective field theory (EFT) methods to Kohn-Sham density functional theory (DFT). When conventional Kohn-Sham…

Nuclear Theory · Physics 2007-05-23 Anirban Bhattacharyya , R. J. Furnstahl

We refine the OrbNet model to accurately predict energy, forces, and other response properties for molecules using a graph neural-network architecture based on features from low-cost approximated quantum operators in the symmetry-adapted…

We present a kinetic-energy density-functional theory and the corresponding kinetic-energy Kohn-Sham (keKS) scheme on a lattice and show that by including more observables explicitly in a density-functional approach already simple…

Chemical Physics · Physics 2018-07-23 Iris Theophilou , Florian Buchholz , F. G. Eich , Michael Ruggenthaler , Angel Rubio

Predicting interfacial thermodynamics across molecular and continuum scales remains a central challenge in computational science. Classical density functional theory (cDFT) provides a first-principles route to connect microscopic…

Computational Physics · Physics 2026-01-01 Edoardo Monti , Peter Yatsyshin , Konstantinos Gkagkas , Andrew B. Duncan

A kinetic energy functional Ee was developed within the framework of the density-functional theory (DFT) based on the energy electron density for the purpose of realizing the orbital-free DFT. The functional includes the nonlocal term…

Computational Physics · Physics 2021-12-06 Hideaki Takahashi

We present OrbNet Denali, a machine learning model for electronic structure that is designed as a drop-in replacement for ground-state density functional theory (DFT) energy calculations. The model is a message-passing neural network that…

Deep-learning density functional theory (DFT) shows great promise to significantly accelerate material discovery and potentially revolutionize materials research. However, current research in this field primarily relies on data-driven…

Computational Physics · Physics 2024-08-14 Yang Li , Zechen Tang , Zezhou Chen , Minghui Sun , Boheng Zhao , He Li , Honggeng Tao , Zilong Yuan , Wenhui Duan , Yong Xu

We present a $\Delta$-machine learning model for obtaining Kohn-Sham accuracy from orbital-free density functional theory (DFT) calculations. In particular, we employ a machine learned force field (MLFF) scheme based on the kernel method to…

Chemical Physics · Physics 2023-10-11 Shashikant Kumar , Xin Jing , John E. Pask , Andrew J. Medford , Phanish Suryanarayana

Two types of approaches to modeling molecular systems have demonstrated high practical efficiency. Density functional theory (DFT), the most widely used quantum chemical method, is a physical approach predicting energies and electron…

Chemical Physics · Physics 2020-03-02 Anton V. Sinitskiy , Vijay S. Pande

Kohn-Sham density functional theory (KS-DFT) has found widespread application in accurate electronic structure calculations. However, it can be computationally demanding especially for large-scale simulations, motivating recent efforts…

Computational Physics · Physics 2024-06-25 Feitong Song , Ji Feng

The design of better exchange-correlation functionals for Density Functional Theory (DFT) is a central challenge of modern electronic structure theory. However, current developments are limited by the mathematical form of the functional,…

Chemical Physics · Physics 2024-08-19 Kyle Bystrom , Boris Kozinsky

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

This work presents an alternative, general, and in-principle exact extension of electronic Kohn-Sham density functional theory (KS-DFT) to the fully quantum-mechanical molecular problem. Unlike in existing multi-component or…

Chemical Physics · Physics 2024-05-14 Emmanuel Fromager , Benjamin Lasorne

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

We present an extension of reverse engineered Kohn-Sham potentials from a density matrix renormalization group calculation towards the construction of a density functional theory functional via deep learning. Instead of applying machine…

Disordered Systems and Neural Networks · Physics 2021-05-05 Peter Schmitteckert

In contrast to the original Kohn-Sham (KS) formalism, we propose a density functional theory (DFT) with fractional orbital occupations for the study of ground states of many-electron systems, wherein strong static correlation is shown to be…

Chemical Physics · Physics 2015-06-03 Jeng-Da Chai

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

Accurate description of deformed atomic nuclei by the orbital-free density functional theory has been a longstanding textbook challenge, due to the difficulty in accounting for the intricate quantum shell effects that are present in such…

Nuclear Theory · Physics 2024-12-31 X. H. Wu , Z. X. Ren , P. W. Zhao

One of the potential applications of a quantum computer is solving quantum chemical systems. It is known that one of the fastest ways to obtain somewhat accurate solutions classically is to use approximations of density functional theory.…

Quantum Physics · Physics 2020-11-18 Thomas E. Baker , David Poulin