方法对比
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| 紧束缚模型× | 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≠ | 1954 | 1965 |
| 提出者≠ | John Slater and George Koster | Walter Kohn |
| 类型≠ | Simplified electronic structure model | Electronic structure method |
| 开创性文献≠ | Slater, J. C., Koster, G. F. (1954). Simplified LCAO method for the periodic potential problem. Physical Review, 94, 1498–1524. DOI ↗ | Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138. DOI ↗ |
| 别名 | TB model, hopping model | DFT, Kohn-Sham equations |
| 相关≠ | 3 | 4 |
| 摘要≠ | The Tight-Binding (TB) model is a simplified semi-empirical approach for computing electronic band structures and properties of solids. Formulated by Slater and Koster in 1954, TB treats electron hopping between atomic sites as the dominant interaction, enabling efficient calculations of band dispersion for a wide variety of materials. | 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. |
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