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

Materials Science · Physics 2025-12-02 Karan Shah , Attila Cangi

The real-time electronic dynamics on material surfaces is critically important to a variety of applications. However, their simulations have remained challenging for conventional methods such as the time-dependent density-functional theory…

Chemical Physics · Physics 2015-06-16 Rulin Wang , Dong Hou , Xiao Zheng

Ultrafast electronic dynamics in solids lies at the core of modern condensed matter and materials physics. To build up a practical ab initio method for studying solids under photoexcitation, we develop a momentum-resolved real-time time…

Materials Science · Physics 2018-10-17 Chao Lian , Shi-Qi Hu , Meng-Xue Guan , Sheng Meng

We present the theory, implementation, and benchmarking of a real-time time-dependent density functional theory (RT-TDDFT) module within the RMG code, designed to simulate the electronic response of molecular systems to external…

Various ways to analyze the dynamical response of clusters and molecules to electromagnetic perturbations exist. Particularly rich information can be obtained from measuring the properties of electrons emitted in the course of the…

Atomic and Molecular Clusters · Physics 2015-06-11 P. Wopperer , P. M. Dinh , P. -G. Reinhard , E. Suraud

We present an application of our new theoretical formulation of quantum dynamics, moment propagation theory (MPT) (Boyer et al., J. Chem. Phys. 160, 064113 (2024)), for employing machine-learning techniques to simulate the quantum dynamics…

Chemical Physics · Physics 2024-12-09 Nicholas J. Boyer , Christopher Shepard , Ruiyi Zhou , Jianhang Xu , Yosuke Kanai

Time-dependent density-functional theory (TDDFT) is widely used to describe electronic excitations in complex finite systems with large numbers of atoms, such as biomolecules and nanocrystals. The first part of this paper will give a simple…

Materials Science · Physics 2008-08-15 C. A. Ullrich , V. Turkowski

Time-dependent density-functional theory (TDDFT) is an extension of ground-state density-functional theory which allows the treatment of electronic excited states and a wide range of time-dependent phenomena in the linear and nonlinear…

Materials Science · Physics 2025-10-10 Carsten A. Ullrich

We propose a machine learning based approach to develop the exchange-correlation potential of time dependent density functional theory (TDDFT). The neural network projection from the time-varying electron densities to the corresponding…

Computational Physics · Physics 2020-05-20 Yasumitsu Suzuki , Ryo Nagai , Jun Haruyama

This chapter provides a basic introduction to excited-state extensions of density functional theory (DFT), including time-dependent (TD-)DFT in both its linear-response and its explicitly time-dependent formulations. As applied to the…

Chemical Physics · Physics 2023-05-02 John M. Herbert

X-ray Thomson scattering (XRTS) constitutes an essential technique for diagnosing material properties under extreme conditions, such as high pressures and intense laser heating. Time-dependent density functional theory (TDDFT) is one of the…

We investigate the time an electronic excitation travels in a supermolecular setup using a measurement process in an open quantum-system framework. The approach is based on the stochastic Schr\"odinger equation and uses a Hamiltonian from…

Materials Science · Physics 2013-12-09 Dirk Hofmann , Heiko Appel , Massimiliano Di Ventra , Stephan Kümmel

Electronic response properties of high-energy density (HED) systems influence planetary structure, drive evolution of fusion targets, and underpin diagnostics in laboratory astrophysics. Real-time time-dependent density functional theory…

Plasma Physics · Physics 2025-11-19 Alina Kononov , Minh Nguyen , Andrew D. Baczewski

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

Real-time time-dependent density functional theory (RT-TDDFT) is known to be hindered by the very small time step (attosecond or smaller) needed in the numerical simulation due to the fast oscillation of electron wavefunctions, which…

Computational Physics · Physics 2018-10-25 Weile Jia , Dong An , Lin-Wang Wang , Lin Lin

Real-Time Time-Dependent Density Functional Theory (TDDFT) has become an attractive tool to model quantum dynamics on a first-principles Density Functional Theory level. In recent years, several developments and applications in this field…

Computational Physics · Physics 2020-08-21 Joscha Hekele , Peter Kratzer

Time-dependent density functional theory (TDDFT) is a standard approach for calculating optical excitations of molecules and solids, while ensemble DFT (EDFT) is a promising alternative under development. We introduce ensemble TDDFT…

Chemical Physics · Physics 2026-05-22 Kimberly J. Daas , Steven Crisostomo , Kieron Burke

Time-dependent density-functional theory (TDDFT) is deemed to be a formally rigorous way of dealing with the time-evolution of a many-electron system at the level of electron densities rather than the underlying wavefunctions, which in turn…

Chemical Physics · Physics 2024-11-26 Jochen Schirmer

Time-dependent density functional theory (TDDFT) is presently enjoying enormous popularity in quantum chemistry, as a useful tool for extracting electronic excited state energies. This article discusses how TDDFT is much broader in scope,…

Other Condensed Matter · Physics 2007-05-23 Kieron Burke , Jan Werschnik , E. K. U. Gross

Efficient molecular dynamics (MD) simulation is vital for understanding atomic-scale processes in materials science and biophysics. Traditional density functional theory (DFT) methods are computationally expensive, which limits the…

Machine Learning · Computer Science 2025-10-03 Hung Le , Sherif Abbas , Minh Hoang Nguyen , Van Dai Do , Huu Hiep Nguyen , Dung Nguyen
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