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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

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

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 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

Real-time, time-dependent density functional theory (RT-TDDFT) has gained popularity as a first-principles approach to study a variety of excited-state phenomena such as optical excitations and electronic stopping. Within RT-TDDFT…

Materials Science · Physics 2019-07-23 Dillon C. Yost , Yi Yao , Yosuke Kanai

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

Molecular absorption and photo-electron spectra can be efficiently predicted with real-time time-dependent density-functional theory (TDDFT). We show here how these techniques can be easily extended to study time-resolved pump-probe…

Atomic and Molecular Clusters · Physics 2013-01-10 Umberto De Giovannini , Gustavo Brunetto , Alberto Castro , Jessica Walkenhorst , Angel Rubio

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

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…

A mixed quantum-classical approach to simulate the coupled dynamics of electrons and nuclei in nanoscale molecular systems is presented. The method relies on a second order expansion of the Lagrangian in time-dependent density functional…

Chemical Physics · Physics 2009-11-10 T. A. Niehaus , D. Heringer , B. Torralva , Th. Frauenheim

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

A practical computational scheme based on time-dependent density functional theory (TDDFT) and ultrasoft pseudopotential (USPP) is developed to study electron dynamics in real time. A modified Crank-Nicolson time-stepping algorithm is…

Materials Science · Physics 2007-05-23 Xiaofeng Qian , Ju Li , Xi Lin , Sidney Yip

Spectroscopic properties of molecules holds great importance for the description of the molecular response under the effect of an UV/Vis electromagnetic radiation. Computationally expensive ab initio (e.g. MultiConfigurational SCF, Coupled…

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

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

Machine learning thermodynamic perturbation theory (MLPT) is a promising approach to compute finite temperature properties when the goal is to compare several different levels of ab initio theory and/or to apply highly expensive…

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

The construction of a better exchange-correlation potential in time-dependent density functional theory (TDDFT) can improve the accuracy of TDDFT calculations and provide more accurate predictions of the properties of many-electron systems.…

Quantum Physics · Physics 2023-08-23 Jun Yang , James D Whitfield

Nuclear quantum effects and non-Born--Oppenheimer effects play a vital role in many chemical and biological processes, motivating the incorporation of such effects into dynamical simulations. In real-time nuclear--electronic orbital…

Chemical Physics · Physics 2026-05-27 Nicholas J. Boyer , Sharon Hammes-Schiffer

The coupled quantum dynamics of electrons and protons is ubiquitous in many dynamical processes involving light-matter interaction, such as solar energy conversion in chemical systems and photosynthesis. A first-principles description of…

Chemical Physics · Physics 2023-11-07 Jianhang Xu , Ruiyi Zhou , Tao E. Li , Volker Blum , Sharon Hammes-Schiffer , Yosuke Kanai
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