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Related papers: Spin-Adapted TDDFT

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Time-Dependent Density Functional Theory (TDDFT) has recently been extended to describe many-body open quantum systems (OQS) evolving under non-unitary dynamics according to a quantum master equation. In the master equation approach,…

Chemical Physics · Physics 2015-05-18 David G. Tempel , Mark A. Watson , Roberto Olivares-Amaya , Alán Aspuru-Guzik

Density functional theory (DFT) and linear-response time-dependent density functional theory (LR-TDDFT) rely on an exchange-correlation (xc) approximation that provides not only energy but also its functional derivatives that enter the…

Chemical Physics · Physics 2026-04-08 Xiaoyu Zhang

This paper tackles the problem of recovering a low-rank signal tensor with possibly correlated components from a random noisy tensor, or so-called spiked tensor model. When the underlying components are orthogonal, they can be recovered…

Machine Learning · Statistics 2023-03-20 Mohamed El Amine Seddik , Mohammed Mahfoud , Merouane Debbah

A model of dynamic orientation using optimized radiofrequency (RF) irradiation produced perpendicular to the holding field is developed for the spin-1 system required for tensor-polarized fixed-target experiments. The derivation applies to…

Nuclear Theory · Physics 2017-07-25 Dustin Keller

In this work we explore the performance of approximations to electron correlation in reduced density-matrix functional theory (RDMFT) and of approximations to the observables calculated within this theory. Our analysis focuses on the…

Strongly Correlated Electrons · Physics 2015-02-26 Stefano Di Sabatino , Jan A. Berger , Lucia Reining , Pina Romaniello

For electronic systems with multi-reference (MR) character, Kohn-Sham density functional theory (KS-DFT) with the conventional exchange-correlation (xc) energy functionals can lead to incorrect spin densities and related properties. For…

Chemical Physics · Physics 2024-06-14 Yu-Yang Wang , Jeng-Da Chai

Time-dependent density-functional theory (TDDFT) is a powerful tool to study the non-equilibrium dynamics of inhomogeneous interacting many-body systems. Here we show that the simple adiabatic local-spin-density approximation for the…

Strongly Correlated Electrons · Physics 2008-11-11 Wei Li , Gao Xianlong , Corinna Kollath , Marco Polini

Density functional theory (DFT) based modeling of electronic excited states is of importance for investigation of the photophysical/photochemical properties and spectroscopic characterization of large systems. The widely used linear…

Chemical Physics · Physics 2021-05-11 Diptarka Hait , Martin Head-Gordon

Variational excited-state density functional theory (DFT) enables the calculation of excited states at a cost comparable to ground-state calculations, but single-configuration approaches often suffer from spin contamination. We implement…

Chemical Physics · Physics 2026-05-28 Michael J. Sahre , Marco Romanelli , Martijn Marsman , Leticia González , Georg Kresse

Near-degenerate electronic structures remain a major challenge for conventional single-reference density functional theory (DFT). To address this problem, we propose time-dependent $\Delta$SCF (TD$\Delta$SCF), a novel linear-response scheme…

Chemical Physics · Physics 2026-05-12 Shuto Shibasaki , Fumiya Mohri , Takashi Tsuchimochi

We present a practical approach to treat static and dynamical correlation accurately in large multi-configurational systems. The static correlation is accounted for using the spin-flip approach which is well known for capturing static…

Strongly Correlated Electrons · Physics 2021-02-08 Oinam Romesh Meitei , Nicholas J. Mayhall

Real-time time-dependent density functional theory (TDDFT) is widely considered to be the most accurate available method for calculating electronic stopping powers from first principles, but there have been relatively few assessments of the…

Computational Physics · Physics 2024-01-18 Alina Kononov , Alexander J. White , Katarina A. Nichols , S. X. Hu , Andrew D. Baczewski

Despite the variety of available computational approaches, state-of-the-art methods for calculating excitation energies such as time-dependent density functional theory (TDDFT), are computationally demanding and thus limited to moderate…

Chemical Physics · Physics 2022-03-10 Martina Stella , Kritam Thapa , Luigi Genovese , Laura E. Ratcliff

The spin density wave (SDW) state of the uniform electron gas is investigated in the exact exchange approximation of noncollinear spin density functional theory (DFT). Unlike in Hartree-Fock theory, where the uniform paramagnetic state of…

Materials Science · Physics 2009-09-29 S. Kurth , F. G. Eich

We present an approximation scheme for the dielectric response of thermal collisionless plasmas at arbitrary degeneracy. A T-fraction representation is obtained from the known expansions of the real part of the dielectric function for small…

Plasma Physics · Physics 2015-05-13 August Wierling

Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under various external perturbations such as laser fields. In this work, we present a novel approach to accelerate real time TDDFT…

Materials Science · Physics 2024-07-29 Karan Shah , Attila Cangi

We construct and thoroughly study a new integrable example of the AdS/CFT correspondence with Schr\"{o}dinger symmetry. On the gravity side, the supergravity solution depends on two parameters and is obtained by marginally deforming the…

High Energy Physics - Theory · Physics 2022-07-14 George Georgiou , Georgios Itsios , Dimitrios Zoakos

We recently introduced an efficient methodology to perform density-corrected Hartree-Fock density functional theory (DC(HF)-DFT) calculations and an extension to it we called "corrected" HF DFT (C(HF)-DFT). In this work, we take a further…

Chemical Physics · Physics 2023-11-10 Daniel Graf , Alex J. W. Thom

Physics-informed neural networks (PINNs) have been increasingly employed due to their capability of modeling complex physics systems. To achieve better expressiveness, increasingly larger network sizes are required in many problems. This…

Machine Learning · Computer Science 2023-02-28 Ziyue Liu , Xinling Yu , Zheng Zhang

An optimization-based approach for the Tucker tensor approximation of parameter-dependent data tensors and solutions of tensor differential equations with low Tucker rank is presented. The problem of updating the tensor decomposition is…

Optimization and Control · Mathematics 2019-05-31 Lukas Exl