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We present a generalized formalism to describe the optical energy flow and spatially resolved absorption in arbitrarily anisotropic layered structures. The algorithm is capable of treating any number of layers of arbitrarily anisotropic,…

Explicitly-correlated F12 methods are becoming the first choice for high-accuracy molecular orbital calculations, and can often achieve chemical accuracy with relatively small gaussian basis sets. In most calculations, the many three- and…

Chemical Physics · Physics 2016-05-25 Giuseppe M. J. Barca , Pierre-François Loos , Peter M. W. Gill

Kinetic energy functionals of the electronic density are used to model large systems in the context of density functional theory, without the need to obtain electronic wavefunctions. We discuss the problems associated with the application…

Condensed Matter · Physics 2009-11-07 Nicholas Choly , Efthimios Kaxiras

Super-resolution is generally referred to as the task of recovering fine details from coarse information. Motivated by applications such as single-molecule imaging, radar imaging, etc., we consider parameter estimation of complex…

Information Theory · Computer Science 2016-08-10 Dehui Yang , Gongguo Tang , Michael B. Wakin

We present a new theory for partitioning simulations of periodic and solid-state systems into physically sound atomic contributions at the level of Kohn-Sham density functional theory. Our theory is based on spatially localized linear…

Chemical Physics · Physics 2024-10-01 Luna Zamok , Janus J. Eriksen

Hybrid density functional approximations (DFAs) offer compelling accuracy for ab initio electronic-structure simulations of molecules, nanosystems, and bulk materials, addressing some deficiencies of computationally cheaper, frequently used…

We introduce a local machine-learning method for predicting the electron densities of periodic systems. The framework is based on a numerical, atom-centred auxiliary basis, which enables an accurate expansion of the all-electron density in…

Chemical Physics · Physics 2021-11-10 Alan M. Lewis , Andrea Grisafi , Michele Ceriotti , Mariana Rossi

Deep learning techniques have opened a new venue for electronic structure theory in recent years. In contrast to traditional methods, deep neural networks provide much more expressive and flexible wave function ansatz, resulting in better…

Chemical Physics · Physics 2021-09-08 Xiang Li , Cunwei Fan , Weiluo Ren , Ji Chen

For molecules and solids containing heavy elements, accurate electronic structure calculations require accounting not only for electronic correlations but also for relativistic effects. In molecules, relativity can lead to severe changes in…

Chemical Physics · Physics 2025-10-17 Gaurav Harsha , Vibin Abraham , Dominika Zgid

We propose an adaptive planewave method for eigenvalue problems in electronic structure calculations. The method combines a priori convergence rates and accurate a posteriori error estimates into an effective way of updating the energy…

Computational Physics · Physics 2021-07-30 Beilei Liu , Huajie Chen , Geneviève Dusson , Jun Fang , Xingyu Gao

Recent advances in machine-learned interatomic potentials largely benefit from the atomistic representation and locally invariant many-body descriptors. It was however recently argued that including three- (or even four-) body features is…

Chemical Physics · Physics 2021-10-14 Yaolong Zhang , Junfan Xia , Bin Jiang

A proper theoretical description of electronic structure of the 3d orbitals in the metal centers of functional metalorganics is a challenging problem. In this letter, we apply density functional theory and an exact diagonalization method in…

We present calculations of the hyperfine coupling constants for all the heteronuclear alkali-metal diatomic molecules at the equilibrium geometry of the electronic ground state. These constants are important in developing methods to control…

Atomic Physics · Physics 2017-11-01 J. Aldegunde , J. M. Hutson

Size effects are ubiquitous in the structural, mechanical, and physical properties of materials, making it highly desirable to study the intrinsic properties of thick objects through high-resolution structural analysis in transmission…

Materials Science · Physics 2025-02-26 Wenfeng Yang , Haozhi Sha , Jizhe Cui , Rong Yu

The complex nature of electron-electron correlations is made manifest in the very simple but non-trivial problem of two electrons confined within a sphere. The description of highly non-local correlation and self-interaction effects by…

Other Condensed Matter · Physics 2016-08-16 J. Jung , P. García-González , J. E. Alvarellos , R. W. Godby

We discuss our new implementation of the Real-space Electronic Structure method for studying the atomic and electronic structure of infinite periodic as well as finite systems, based on density functional theory. This improved version which…

Materials Science · Physics 2009-10-31 U. V. Waghmare , Hanchul Kim , I. J. Park , Normand Modine , P. Maragakis , Efthimios Kaxiras

Quantifying material mass and electron density from computed tomography (CT) reconstructions can be highly valuable in certain medical practices, such as radiation therapy planning. However, uniquely parameterising the X-ray attenuation in…

Medical Physics · Physics 2019-04-30 Jonathan H. Mason , Alessandro Perelli , William H. Nailon , Mike E. Davies

We present a computational scheme for ab initio total-energy calculations of materials with strongly interacting electrons using a plane-wave basis set. It combines ab initio band structure and dynamical mean-field theory and is implemented…

Strongly Correlated Electrons · Physics 2015-05-14 I. Leonov , Dm. Korotin , N. Binggeli , V. I. Anisimov , D. Vollhardt

Density functional theory (DFT) provides a theoretical framework for efficient and fairly accurate calculations of the electronic structure of molecules and crystals. The main features of density functional theory are described and DFT…

Chemical Physics · Physics 2012-06-12 Hauke Paulsen , Alfred Xaver Trautwein

The electron density of a molecule or material has recently received major attention as a target quantity of machine-learning models. A natural choice to construct a model that yields transferable and linear-scaling predictions is to…

Chemical Physics · Physics 2022-06-29 Andrea Grisafi , Alan M. Lewis , Mariana Rossi , Michele Ceriotti