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Time-dependent orbital-free DFT is an efficient method for calculating the dynamic properties of large scale quantum systems due to the low computational cost compared to standard time-dependent DFT. We formalize this method by mapping the…

Chemical Physics · Physics 2021-06-09 Kaili Jiang , Michele Pavanello

The 2p-3d core hole interaction in the L2,3 absorption spectra of the 3d transition metals is treated within time-dependent density functional theory (TDDFT). A simple three-level model explains the origin of the strong deviations from the…

Materials Science · Physics 2009-11-11 A. Scherz , E. K. U. Gross , H. Appel , C. Sorg , K. Baberschke , H. Wende , K. Burke

We consider an analytically solvable model of two interacting electrons that allows for the calculation of the exact exchange-correlation kernel of time-dependent density functional theory. This kernel, as well as the corresponding density…

Strongly Correlated Electrons · Physics 2017-05-04 Luis Cort , Daniel Karlsson , Giovanna Lani , Robert van Leeuwen

Time-dependent current-density-functional theory (TDCDFT) provides an in principle exact scheme to calculate efficiently response functions for a very broad range of applications. However, the lack of approximations valid for a range of…

Strongly Correlated Electrons · Physics 2015-05-20 Matteo Gatti

Autoionizing resonances that arise from the interaction of a bound single-excitation with the continuum can be accurately captured with the presently used approximations in time-dependent density functional theory (TDDFT), but those arising…

Materials Science · Physics 2019-03-27 August J. Krueger , Neepa T. Maitra

A nonparametric kernel density estimator for directional-linear data is introduced. The proposal is based on a product kernel accounting for the different nature of both (directional and linear) components of the random vector. Expressions…

We present a family of kernels for analysis of data generated by dynamical systems. These so-called cone kernels feature an explicit dependence on the dynamical vector field operating in the phase-space manifold, estimated empirically…

Dynamical Systems · Mathematics 2014-03-04 Dimitrios Giannakis

[Background:] Recent work found that core excitation can be important in extracting structure information from (d,p) reactions. [Purpose:] Our objective is to systematically explore the role of core excitation in (d,p) reactions, and…

Nuclear Theory · Physics 2016-11-09 A. Deltuva , A. Ross , E. Norvaišas , F. M. Nunes

We investigate a number of formal properties of the adiabatic strictly-correlated electrons (SCE) functional, relevant for time-dependent potentials and for kernels in linear response time-dependent density functional theory. Among the…

Strongly Correlated Electrons · Physics 2016-08-24 Giovanna Lani , Simone di Marino , Augusto Gerolin , Robert van Leeuwen , Paola Gori-Giorgi

The Bethe-Salpeter equation (BSE) that results from the GW approximation to the self-energy is a frequency-dependent (nonlinear) eigenvalue problem due to the dynamically screened Coulomb interaction between electrons and holes. The…

Materials Science · Physics 2022-02-16 Sylvia J. Bintrim , Timothy C. Berkelbach

We calculate the optical properties of a series of passivated non-stoichiometric CdSe clusters using two first-principles approaches: time-dependent density functional theory within the local density approximation, and by solving the…

Materials Science · Physics 2007-05-23 Marie Lopez del Puerto , Murilo L. Tiago , James R. Chelikowsky

Three-body nuclear reactions in two-nucleon plus core systems are described in the framework of exact scattering equations including the core excitation. A nucleon-core optical potential is constructed that can be easily adjusted to the…

Nuclear Theory · Physics 2015-02-18 A. Deltuva

Two-point fermionic propagators in strongly-correlated media are considered with an emphasis on the dynamical interaction kernels of their equations of motion (EOM). With the many-body Hamiltonian confined by a two-body interaction, the…

Nuclear Theory · Physics 2024-02-13 Elena Litvinova

We investigate optical absorption spectra obtained through time-dependent density functional theory (TD-DFT) based on nonempirical hybrid functionals that are designed to correctly reproduce the dielectric function. The comparison with…

Materials Science · Physics 2020-08-17 Alexey Tal , Peitao Liu , Georg Kresse , Alfredo Pasquarello

Adiabatic time-dependent density functional theory fails for excitations of a heteroatomic molecule composed of two open-shell fragments at large separation. Strong frequency-dependence of the exchange-correlation kernel is necessary for…

Other Condensed Matter · Physics 2009-11-11 Neepa T. Maitra , David G. Tempel

The kinetic energy (KE) kernel, which is defined as the second order functional derivative of the KE functional with respect to density, is the key ingredient to the construction of KE models for orbital free density functional theory…

Materials Science · Physics 2025-05-15 Zhandos A. Moldabekov , Xuecheng Shao , Michele Pavanello , Jan Vorberger , Tobias Dornheim

We formulate a rigorous method for calculating a nonadiabatic (frequency-dependent) exchange-correlation (XC) kernel required for correct description of both equilibrium and nonequilibrium properties of strongly correlated systems within…

Strongly Correlated Electrons · Physics 2014-10-13 Volodymyr Turkowski , Talat S. Rahman

Density matrix embedding theory (DMET) provides a framework to describe ground-state expectation values in strongly correlated systems, but its extension to dynamical quantities is still an open problem. We show one route to obtaining…

Strongly Correlated Electrons · Physics 2025-11-13 Shuoxue Li , Chenghan Li , Huanchen Zhai , Garnet Kin-Lic Chan

Recent studies have shown that functional brain brainwork is dynamic even during rest. A common approach to modeling the brain network in whole brain resting-state fMRI is to compute the correlation between anatomical regions via sliding…

We present a novel attention-based model for discrete event data to capture complex non-linear temporal dependence structures. We borrow the idea from the attention mechanism and incorporate it into the point processes' conditional…

Machine Learning · Statistics 2021-02-23 Shixiang Zhu , Minghe Zhang , Ruyi Ding , Yao Xie