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Realistic prediction of the superconducting transition temperature (Tc) for PdH is a long-standing challenge, because it depends on robust calculations of the electron and phonon band structures to obtain the electron-phonon scattering…

Materials Science · Physics 2022-08-08 Samaneh Sadat Setayandeh , Tim Gould , Toktam Morshedloo , Evan Gray

Time-dependent density-functional theory (TDDFT) treats dynamical exchange and correlation (xc) via a single-particle potential, Vxc(r,t), defined as a nonlocal functional of the density n(r',t'). The popular adiabatic local-density…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 C. A. Ullrich , I. V. Tokatly

We present the theory and implementation of a fully variational wave function -- density functional theory (DFT) hybrid model, which is applicable to many cases of strong correlation. We denote this model the multiconfigurational…

An exact theoretical framework based on Time Dependent Density Functional Theory (TDDFT) is proposed in order to deal with the time-dependent quantum transport in fully interacting systems. We use a \textit{partition-free} approach by Cini…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Gianluca Stefanucci , Carl-Olof Almbladh

We find the analytical solution to the time-dependent density-functional theory (TDDFT) problem for the quasi-low-dimensional (2D and 1D) electron gas (QLDEG) with only one band filled in the direction perpendicular to the system extent.…

Mesoscale and Nanoscale Physics · Physics 2017-06-14 Vladimir U. Nazarov

In this work, we derive a multi-fragment real-time extension of projected density matrix embedding theory (pDMET) designed to treat non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static…

Strongly Correlated Electrons · Physics 2023-04-19 Dariia Yehorova , Joshua S. Kretchmer

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

Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical systems. Previous works have attempted to accelerate LR-TDDFT using heterogeneous…

Hardware Architecture · Computer Science 2025-04-07 Qingcai Jiang , Buxin Tu , Xiaoyu Hao , Junshi Chen , Hong An

Multireference density functional theory (MR-DFT) has been a pivotal method for studying nuclear low-lying states and neutrinoless double-beta ($0\nu\beta\beta$) decay. However, quantifying their theoretical uncertainties has been a…

Nuclear Theory · Physics 2025-08-26 X. Zhang , C. C. Wang , C. R. Ding , J. M. Yao

We have carried out a thorough benchmark of the FDE-ET method for calculating hole transfer couplings. We have considered 10 exchange-correlation functionals, 3 non-additive kinetic energy functionals and 3 basis sets. Overall, we conclude…

Chemical Physics · Physics 2015-03-02 Pablo Ramos , Markos Papadakis , Michele Pavanello

In principle, we should not need the time-dependent extension of density-functional theory (TDDFT) for excitations, and in particular not for Molecular Dynamics (MD) studies: the theorem by Hohenberg and Kohn teaches us that for any…

Strongly Correlated Electrons · Physics 2015-05-27 J. L. Alonso , Alberto Castro , Pablo Echenique , Angel Rubio

New energy-density functionals (EDFs) inspired by effective-field theories (EFTs) have been recently proposed. The present work focuses on three of such functionals which were developed to produce satisfactory equations of state for nuclear…

Nuclear Theory · Physics 2018-09-26 Jérémy Bonnard , Marcella Grasso , Denis Lacroix

A major challenge in using spin-flip time-dependent density functional theory (SF-TD-DFT) for spin-flip-down excitations is the presence of spin contamination. While several improved methods have been developed in the past, a simple and…

Chemical Physics · Physics 2025-11-24 Hewang Zhao , Zhendong Li

The low energy band structure near the band gap determines the electrical performance of thermoelectric materials. Here, by using the hybrid-density functional theory (hybrid-DFT) calculations, we calculate the low energy band structure of…

Materials Science · Physics 2017-04-19 Sudong Park , Byungki Ryu

Simultaneous wireless information and power transfer (SWIPT) provides a promising solution for enabling perpetual wireless networks. As energy efficiency (EE) is an im- portant evaluation of system performance, this thesis studies…

Information Theory · Computer Science 2015-04-10 Shiyang Leng

Nanoscale electronic transport is of intense technological interest, with applications ranging from semiconducting devices and molecular junctions to charge migration in biological systems. Most explicit theoretical approaches treat…

Mesoscale and Nanoscale Physics · Physics 2014-08-08 Justin E. Elenewski , Hanning Chen

In this work we have studied a new functional for the correlation energy obtained from the exact-exchange (EXX) approximation within time-dependent density functional theory (TDDFT). Correlation energies have been calculated for a number of…

Mesoscale and Nanoscale Physics · Physics 2015-05-14 Maria Hellgren , Ulf von Barth

In this work, for the first time, a density functional theory (DFT) based comprehensive theoretical study is performed on the surface electronic properties of Bi2Se3 nanosheet in the presence of a surface capping layer as well as mechanical…

Materials Science · Physics 2024-12-10 Naresh Bahadursha , Banasree Sadhukhan , Tanay Nag , Swastik Bhattacharya , Sayan Kanungo

We propose a first-principles time-dependent density functional theoretical (TDDFT) approach in momentum (P) space for quantitative study of electron transport in molecular devices under arbitrary biases. In this approach, the basic…

Mesoscale and Nanoscale Physics · Physics 2009-02-10 Zhongyuan Zhou , Shih-I Chu

Transformer-based Diffusion Probabilistic Models (DPMs) have shown more potential than CNN-based DPMs, yet their extensive computational requirements hinder widespread practical applications. To reduce the computation budget of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Xinwang Chen , Ning Liu , Yichen Zhu , Feifei Feng , Jian Tang