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Due to its favorable computational efficiency time-dependent (TD) density functional theory (DFT) enables the prediction of electronic spectra in a high-throughput manner across chemical space. Its predictions, however, can be quite…

We propose a practical approximation to the exchange-correlation functional of (time-dependent) density functional theory for many-electron systems coupled to photons. The (time non-local) optimized effective potential (OEP) equation for…

Mesoscale and Nanoscale Physics · Physics 2015-09-02 Camilla Pellegrini , Johannes Flick , Ilya V. Tokatly , Heiko Appel , Angel Rubio

Lack of memory (locality in time) is a major limitation of almost all present time-dependent density functional approximations. By using semiclassical dynamics to compute correlation effects within a density-matrix functional approach, we…

Chemical Physics · Physics 2015-05-18 A. K. Rajam , I. Raczkowska , N. T. Maitra

Ab initio electronic structure methods give accurate results for small systems, but do not scale well to large systems. Chemical insight tells us that molecular functional groups will behave approximately the same way in all molecules,…

Chemical Physics · Physics 2007-05-23 Benjamin G. Janesko , David Yaron

We study a classical system of identically charged counter-ions near a planar wall carrying a uniform surface charge density. The equilibrium statistical mechanics of the system depends on a single dimensionless coupling parameter. A new…

Soft Condensed Matter · Physics 2019-01-21 I. Palaia , M. Trulsson , L. Samaj , E. Trizac

In this study, a density-on-density regression model is introduced, where the association between densities is elucidated via a warping function. The proposed model has the advantage of a being straightforward demonstration of how one…

Methodology · Statistics 2023-07-10 Yi Zhao , Abhirup Datta , Bohao Tang , Vadim Zipunnikov , Brian S. Caffo

Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain the proper balance between the black-box nature of ML…

Chemical Physics · Physics 2021-11-16 Ksenia R. Briling , Alberto Fabrizio , Clemence Corminboeuf

Electron-phonon coupling (EPC) is key for understanding many properties of materials such as superconductivity and electric resistivity. Although first principles density-functional-theory (DFT) based EPC calculations are used widely, their…

We present a machine learning (ML) method for predicting electronic structure correlation energies using Hartree-Fock input.The total correlation energy is expressed in terms of individual and pair contributions from occupied molecular…

Chemical Physics · Physics 2018-10-16 Matthew Welborn , Lixue Cheng , Thomas F. Miller

We propose a descriptor for molecular electronic structure that is based solely on the one- and two-electron integrals but is translationally, rotationally, and unitarily invariant. Then, directly exploiting size consistency, we train and…

Quantum Physics · Physics 2026-03-02 Valerii Chuiko , Giovanni B. Da Rosa , Paul W. Ayers

We demonstrate the importance of electron correlation effects in the hyperfine structure constants of many low-lying states in $^{210}$Fr and $^{212}$Fr. This is achieved by calculating the magnetic dipole and electric quadrupole hyperfine…

Atomic Physics · Physics 2015-05-20 B. K. Sahoo , D. K. Nandy , B. P. Das , Y. Sakemi

Groundwater in the Densu Basin is increasingly threatened by heavy metal contamination, but conventional methods fail to capture the statistical complexity and spatial heterogeneity of pollution indicators. A key challenge is modelling the…

Machine Learning · Computer Science 2026-05-04 T. Ansah-Narh , G. Y. Afrifa , J. B. Tandoh , K. Asare , M. Addi , K. E. Yorke , D. M. A. Akpoley , K. Aidoo , S. K. Fosuhene

It was recently shown [Y. Suzuki, L. Lacombe, K. Watanabe, and N. T. Maitra, Phys. Rev. Lett. 119, 263401 (2017)] that peak and valley structures in the exact exchange-correlation potential of time-dependent density functional theory are…

Chemical Physics · Physics 2018-07-04 Lionel Lacombe , Yasumitsu Suzuki , Kazuyuki Watanabe , Neepa T. Maitra

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

Chemical bonding is the stabilization of a composite molecular system caused by different interactions in and between the subsystems, among the strong kinds of bonding is covalent bonding especially important. Characteristic for covalent…

Chemical Physics · Physics 2022-05-03 Alexander F. Sax

We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of thirteen electronic ground-state properties of organic molecules. The performance of each…

New ways to treat electron correlation in electronic structure problems are discussed in the context of many-electron theory. The present work focuses primarily on static correlation. In related work, a method for including dynamical…

Chemical Physics · Physics 2018-09-05 Jerry L. Whitten

Accurately treating strong electron correlation in quantum chemistry typically requires multireference wave-function methods with steep computational scaling. The recently proposed i-DMFT method promises near configuration-interaction…

Chemical Physics · Physics 2026-04-23 Paul G. Graf , Florian Matz , Lexin Ding , Julia Liebert , Markus Penz , Christian Schilling

Methods for estimating the correlation energy of molecules and other electronic systems are discussed based on the assumption that the correlation energy can be partitioned between atomic regions. In one method, the electron density is…

Chemical Physics · Physics 2022-05-16 Jerry L. Whitten

Motivation: Drug discovery demands rapid quantification of compound-protein interaction (CPI). However, there is a lack of methods that can predict compound-protein affinity from sequences alone with high applicability, accuracy, and…

Biomolecules · Quantitative Biology 2020-12-17 Mostafa Karimi , Di Wu , Zhangyang Wang , Yang Shen