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Second-order Moller-Plesset perturbation theory (MP2) provides accurate correlation energies for periodic systems but suffers from finite-size errors (FSEs) that have inverse volume scaling due to the Coulomb kernel singularity in…

Computational Physics · Physics 2026-05-14 Stephen Jon Quiton , Juan D. F. Pottecher , Martin Head-Gordon , Lin Lin

We present an efficient implementation of periodic Gaussian density fitting (GDF) using the Coulomb metric. The three-center integrals are divided into two parts by range-separating the Coulomb kernel, with the short-range part evaluated in…

Chemical Physics · Physics 2021-04-08 Hong-Zhou Ye , Timothy C. Berkelbach

We review two common numerical schemes for Coulomb potential evaluation that differ only in their radial part of the solutions in the spherical harmonic expansion (SHE). One is based on finite-difference method (FDM) while the other is…

Chemical Physics · Physics 2022-05-25 Po-Hao Chang , Zachary Buschmann , Rajendra R. Zope

Separating the Coulomb potential into short-range and long-range components enables the use of different electron repulsion integral algorithms for each component. The short-range part can be efficiently computed using the analytical…

Chemical Physics · Physics 2023-09-27 Qiming Sun

We present an efficient algorithm for the all-electron periodic Coulomb matrix based on the Ewald summation combined with the Fourier-transformed Coulomb method. The short-range contributions involving compact densities are evaluated in…

Chemical Physics · Physics 2025-09-23 Hieu Q. Dinh , Adam Rettig , Xintian Feng , Joonho Lee

Real-time time-dependent density functional theory (RT-TDDFT) is a powerful approach for investigating various ultrafast phenomena in materials. However, most existing RT-TDDFT studies rely on adiabatic local or semi-local approximations,…

Materials Science · Physics 2025-12-23 Yuyang Ji , Haotian Zhao , Peize Lin , Xinguo Ren , Lixin He

Finite-size (FS) effects are a major source of error in many-body (MB) electronic structure calculations of extended systems. A method is presented to correct for such errors. We show that MB FS effects can be effectively included in a…

Materials Science · Physics 2008-03-28 Hendra Kwee , Shiwei Zhang , Henry Krakauer

We develop a stochastic formulation of the optimally-tuned range-separated hybrid density functional theory which enables significant reduction of the computational effort and scaling of the non-local exchange operator at the price of…

Chemical Physics · Physics 2016-09-28 Daniel Neuhauser , Eran Rabani , Yael Cytter , Roi Baer

Self-interaction error (SIE), arising from the imperfect cancellation of the spurious classical Coulomb interaction between an electron and itself, is a persistent challenge in modern density functional approximations. This issue is…

Hybrid density functional theory (DFT) remains intractable for large periodic systems due to the demanding computational cost of exact exchange. We apply the tensor hypercontraction (THC) (or interpolative separable density fitting)…

Computational Physics · Physics 2023-10-13 Adam Rettig , Joonho Lee , Martin Head-Gordon

In this paper, we propose a method to approximate the Gaussian function on ${\mathbb R}$ by a short cosine sum. We generalise and extend the differential approximation method proposed in [4, 40] to approximate $\mathrm{e}^{-t^{2}/2\sigma}$…

Numerical Analysis · Mathematics 2025-05-23 Nadiia Derevianko , Gerlind Plonka

Despite decades of practice, finite-size errors in many widely used electronic structure theories for periodic systems remain poorly understood. For periodic systems using a general Monkhorst-Pack grid, there has been no comprehensive and…

Computational Physics · Physics 2023-11-16 Xin Xing , Xiaoxu Li , Lin Lin

We present a new reciprocal space analytical method to cutoff the long range interactions in supercell calculations for systems that are infinite and periodic in 1 or 2 dimensions, extending previous works for finite systems. The proposed…

Other Condensed Matter · Physics 2009-11-11 Carlo A. Rozzi , Daniele Varsano , Andrea Marini , Eberhard K. U. Gross , Angel Rubio

We present a computationally efficient approach to perform large-scale all-electron density functional theory calculations by enriching the classical finite element basis with compactly supported atom-centered numerical basis functions that…

Computational Physics · Physics 2017-01-11 Bikash Kanungo , Vikram Gavini

We introduce a computationally efficient screening for the Coulomb potential that also allows calculating approximated long-range exact exchange contributions with an accuracy similar to an explicit full-range evaluation of the exact…

Materials Science · Physics 2025-05-06 Sebastian Kokott , Volker Blum , Matthias Scheffler

Ensemble Density Functional Theory (EDFT) is a generalization of ground-state Density Functional Theory (GS DFT), which is based on an exact formal theory of finite collections of a system's ground and excited states. EDFT in various forms…

Materials Science · Physics 2024-08-27 Remi J. Leano , Aurora Pribram-Jones , David A. Strubbe

Simulations in the warm dense matter regime using finite temperature Kohn-Sham density functional theory (FT-KS-DFT), while frequently used, are computationally expensive due to the partial occupation of a very large number of high-energy…

Materials Science · Physics 2018-04-04 Yael Cytter , Eran Rabani , Daniel Neuhauser , Roi Baer

Standard approximations for the exchange-correlation (XC) functional in Kohn-Sham density functional theory (KS-DFT) typically lead to unacceptably large errors when applied to strongly-correlated electronic systems. Partition-DFT (PDFT) is…

Chemical Physics · Physics 2023-09-12 Yi Shi , Yuming Shi , Adam Wasserman

We propose a high-precision numerical quadrature framework based on local Fourier extension (LFE) approximations. The method constructs, on each subinterval, a truncated-SVD stabilized local Fourier continuation of the integrand on an…

Numerical Analysis · Mathematics 2026-03-17 Xinran Liu , Zhenyu Zhao , Benxue Gong

In many contexts Gaussian Mixtures (GM) are used to approximate probability distributions, possibly time-varying. In some applications the number of GM components exponentially increases over time, and reduction procedures are required to…

Machine Learning · Statistics 2021-04-27 A. D'Ortenzio , C. Manes
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