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We introduce an electron-photon exchange-correlation functional for quantum electrodynamical density-functional theory (QEDFT). The approach, photon MBD (pMBD), is inspired by the many-body dispersion (MBD) method for weak intermolecular…

Chemical Physics · Physics 2025-12-23 Cankut Tasci , Leonardo A. Cunha , Johannes Flick

Fast Multipole Methods (FMMs) based on the oscillatory Helmholtz kernel can reduce the cost of solving N-body problems arising from Boundary Integral Equations (BIEs) in acoustic or electromagnetics. However, their cost strongly increases…

Numerical Analysis · Mathematics 2022-02-11 Igor Chollet , Xavier Claeys , Pierre Fortin , Laura Grigori

A storage ring provides an attractive option for directly measuring the electric dipole moment~(EDM) of charged particles. To reach a sensitivity of 10^-29 e x cm, it is critical to mitigate the systematic errors from all sources. This…

Accelerator Physics · Physics 2016-11-16 Mei Bai , Yann Dutheil , David Sagan

We have explored the use of range separation as a possible avenue for further improvement on our revDSD minimally empirical double hybrid functionals. Such $\omega$DSD functionals encompass the XYG3 type of double hybrid (i.e., xDSD) as a…

Chemical Physics · Physics 2021-06-10 Golokesh Santra , Minsik Cho , Jan M. L. Martin

The GMTKN55 data set is a collection of standard benchmarks used in molecular quantum chemistry that spans small- and large-molecule thermochemistry, reaction barriers, and non-covalent interactions. Herein, we identify a flaw in the…

Chemical Physics · Physics 2026-05-22 Kyle R. Bryenton , Erin R. Johnson

This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree-Fock computations. A…

Chemical Physics · Physics 2022-09-21 Jiace Sun , Lixue Cheng , Thomas F. Miller

In this work, we investigate dispersion interactions in a selection of atomic, molecular, and molecule-surface systems, comparing high-level correlated methods with empirically-corrected density functional theory (DFT). We assess the…

Chemical Physics · Physics 2021-01-27 Tyler J. Hughes , Robert A. Shaw , Salvy P. Russo

Accurate exchange-correlation (XC) potentials for 3-dimensional systems -- via solution of the \emph{inverse} density functional theory (DFT) problem -- are now available to test the quality of DFT approximations. Herein, the \emph{exact}…

Chemical Physics · Physics 2021-11-18 Bikash Kanungo , Paul M. Zimmerman , Vikram Gavini

Kohn-Sham Density Functional Theory (KS-DFT) provides the exact ground state energy and electron density of a molecule, contingent on the as-yet-unknown universal exchange-correlation (XC) functional. Recent research has demonstrated that…

Dynamical Mean-Field Theory (DMFT) has opened new perspectives for the investigation of strongly correlated electron systems and greatly improved our understanding of correlation effects in models and materials. In contrast to…

Strongly Correlated Electrons · Physics 2020-07-16 Dieter Vollhardt

We investigate the description of excitonic effects within time-dependent density-functional theory (TDDFT). The exchange-correlation kernel f_xc introduced in TDDFT allows a clear separation of quasiparticle and excitonic effects. Using a…

Other Condensed Matter · Physics 2007-05-23 R. Stubner , I. V. Tokatly , O. Pankratov

Ab initio molecular dynamics (AIMD) based on density functional theory (DFT) is a powerful approach for modeling molten salts. However, standard exchange-correlation functionals often neglect dispersion interactions, introducing potential…

Materials Science · Physics 2026-04-23 Shubhojit Banerjee , Rajni Chahal-Crockett , Julian Barra , Stephen T Lam

The paper describes the coupling of the MercuryDPM discrete element method (DEM) code and the implementation of the kernel-independent fast multipole method (KIFMM). The combined simulation framework allows addressing the large class of…

Soft Condensed Matter · Physics 2025-12-11 Igor A. Ostanin

We combine a regularized variant of the strongly constrained and appropriately normed semilocal density functional [J. Sun, A. Ruzsinszky, and J. P. Perdew, Phys. Rev. Lett. 115, 036402 (2015)] with the latest generation semi-classical…

Distributed point charge models (DCM) and their minimal variants (MDCM) have been integrated with tools widely used for condensed-phase simulations, including a virial-based barostat and a slow-growth algorithm for thermodynamic…

Chemical Physics · Physics 2020-11-03 Mike Devereux , Marco Pezzella , Shampa Raghunathan , Markus Meuwly

Permanent electric dipole moments (EDMs) of fundamental particles such as the electron are signatures of parity and time-reversal violation due to physics beyond the standard model. EDM measurements probe new physics at energy scales well…

Atomic Physics · Physics 2020-10-09 Mohit Verma , Andrew M. Jayich , Amar C. Vutha

We assess the accuracy of common hybrid exchange-correlation (XC) functionals (PBE0, PBE0-1/3, HSE06, HSE03, and B3LYP) within Kohn-Sham density functional theory (KS-DFT) for the harmonically perturbed electron gas at parameters relevant…

Chemical Physics · Physics 2023-03-08 Zhandos A. Moldabekov , Mani Lokamani , Jan Vorberger , Attila Cangi , Tobias Dornheim

We study the lattice dynamics of iron superconductor FeSe, and address the fundamental question of how important is proper description of fluctuating magnetic moments in metallic systems for phonon dispersion and phonon density of states.…

Strongly Correlated Electrons · Physics 2021-01-04 Ghanashyam Khanal , Kristjan Haule

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

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