Methoden vergleichen

	Zeitabhängige DFT	Dichtefunktionaltheorie
Fachgebiet	Quantencomputing	Quantencomputing
Familie	Machine learning	Machine learning
Entstehungsjahr	1984	1965
Urheber	Erich Runge and Eberhard Gross	Walter Kohn
Typ	Excited state method	Electronic structure method
Wegweisende Quelle	Runge, E., Gross, E. K. (1984). Density-functional theory for time-dependent systems. Physical Review Letters, 52, 997–1000.	Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138.
Aliasnamen	TDDFT, TDDFT/DFT	DFT, Kohn-Sham equations
Verwandt	3	4
Zusammenfassung	Time-Dependent Density Functional Theory (TDDFT) extends DFT to excited states and time-dependent phenomena. Formulated by Runge and Gross in 1984, TDDFT enables calculation of excitation energies, optical spectra, and charge-transfer processes with moderate computational cost, making it invaluable for photochemistry and materials science.	Density Functional Theory (DFT) is a computational method for determining the properties of materials and molecules by modeling the ground state electron density. Developed by Walter Kohn and Lu Jeu Sham in the 1960s, DFT reduces the complexity of quantum chemistry from tracking individual electron coordinates to optimizing the total electron density, enabling efficient simulations of large molecular and condensed-matter systems.