方法对比
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| 密度泛函理论× | 时变密度泛函理论× | |
|---|---|---|
| 领域 | 量子计算 | 量子计算 |
| 方法族 | Machine learning | Machine learning |
| 起源年份≠ | 1965 | 1984 |
| 提出者≠ | Walter Kohn | Erich Runge and Eberhard Gross |
| 类型≠ | Electronic structure method | Excited state method |
| 开创性文献≠ | Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138. DOI ↗ | Runge, E., Gross, E. K. (1984). Density-functional theory for time-dependent systems. Physical Review Letters, 52, 997–1000. DOI ↗ |
| 别名 | DFT, Kohn-Sham equations | TDDFT, TDDFT/DFT |
| 相关≠ | 4 | 3 |
| 摘要≠ | 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. | 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. |
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