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We use machine learning methods to approximate a classical density functional. As a study case, we choose the model problem of a Lennard Jones fluid in one dimension where there is no exact solution available and training data sets must be…

Soft Condensed Matter · Physics 2019-03-04 Shang-Chun Lin , Martin Oettel

Energy functionals serve as the basis for different models and methods in quantum and classical many-particle physics. Arguably, one of the most successful and widely used approaches in material science at both ambient and extreme…

Plasma Physics · Physics 2024-10-22 Z. Moldabekov , J. Vorberger , T. Dornheim

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semi-local density functional theory (DFT), and thereby furnish a more accurate and reliable description of the electronic structure in…

Computational Physics · Physics 2021-05-10 Hsin-Yu Ko , Junteng Jia , Biswajit Santra , Xifan Wu , Roberto Car , Robert A. DiStasio

We propose hybrid schemes incorporating exact exchange into thermally-assisted-occupation density functional theory (TAO-DFT) [J.-D. Chai, J. Chem. Phys. 136, 154104 (2012)] for an improved description of nonlocal exchange effects. With a…

Chemical Physics · Physics 2017-01-24 Jeng-Da Chai

Combining classical density functional theory (cDFT) with quantum mechanics (QM) methods offers a computationally efficient alternative to traditional QM/molecular mechanics (MM) approaches for modeling mixed quantum-classical systems at…

Statistical Mechanics · Physics 2026-02-17 Guillaume Jeanmairet , Maxime Labat , Emmanuel Giner

Over the last few decades, classical density-functional theory (DFT) and its dynamic extensions (DDFTs) have become powerful tools in the study of colloidal fluids. Recently, previous DDFTs for spherically-symmetric particles have been…

Statistical Mechanics · Physics 2016-08-02 Miguel A. Durán-Olivencia , Benjamin D. Goddard , Serafim Kalliadasis

The stochastic density functional theory (DFT) [Phys. Rev. Lett. 111, 106402 (2013)] is a valuable linear scaling approach to Kohn-Sham DFT that does not rely on the sparsity of the density matrix. Linear (and often sub-linear) scaling is…

Chemical Physics · Physics 2019-02-20 Ming Chen , Roi Baer , Daniel Neuhauser , Eran Rabani

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

Ensemble density functional theory (eDFT) is an exact time-independent alternative to time-dependent DFT (TD-DFT) for the calculation of excitation energies. Despite its formal simplicity and advantages in contrast to TD-DFT (multiple…

Strongly Correlated Electrons · Physics 2017-01-19 Killian Deur , Laurent Mazouin , Emmanuel Fromager

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

Starting from Newton's equations of motion, we derive a dynamical density functional theory (DDFT) applicable to atomic liquids. The theory has the feature that it requires as input the Helmholtz free energy functional from equilibrium…

Soft Condensed Matter · Physics 2007-05-23 A. J. Archer

A formulation of the density functional theory is constructed on the foundations of entropic inference. The theory is introduced as an application of maximum entropy for inhomogeneous fluids in thermal equilibrium. It is shown that entropic…

Statistical Mechanics · Physics 2023-12-29 Ahmad Yousefi , Ariel Caticha

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

We propose an approach that links density functional theory (DFT) and molecular dynamics (MD) simulation to study fluid behavior in nanopores in contact with bulk (macropores). It consists of two principal steps. First, the theoretical…

Computational Physics · Physics 2021-07-06 Mariia Vaganova , Irina Nesterova , Yuriy Kanygin , Andrey Kazennov , Aleksey Khlyupin

A unified formulation of the density functional theory is constructed on the foundations of entropic inference in both the classical and the quantum regimes. The theory is introduced as an application of entropic inference for inhomogeneous…

Statistical Mechanics · Physics 2021-12-20 Ahmad Yousefi

Dynamical Mean-Field Theory (DMFT) has established itself as a reliable and well-controlled approximation to study correlation effects in bulk solids and also two-dimensional systems. In combination with standard density-functional theory…

Atomic and Molecular Clusters · Physics 2015-05-30 V. Turkowski , A. Kabir , N. Nayyar , Talat S. Rahman

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

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

While density functional theory (DFT) serves as a prevalent computational approach in electronic structure calculations, its computational demands and scalability limitations persist. Recently, leveraging neural networks to parameterize the…

Computational Physics · Physics 2024-06-18 Yang Zhong , Hongyu Yu , Jihui Yang , Xingyu Guo , Hongjun Xiang , Xingao Gong

Two-dimensional mixtures of dipolar colloidal particles with different dipole moments exhibit extremely rich self-assembly behaviour and are relevant to a wide range of experimental systems, including charged and super-paramagnetic colloids…

Soft Condensed Matter · Physics 2019-04-16 W. R. C. Somerville , J. L. Stokes , A. M. Adawi , T. S. Horozov , A. J. Archer , D. M. A. Buzza