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밀도 범함수 이론×Hartree-Fock (HF) 방법×Tight-Binding Model×
분야양자컴퓨팅양자컴퓨팅양자컴퓨팅
계열Machine learningMachine learningMachine learning
기원 연도196519281954
창시자Walter KohnDouglas Hartree and Vladimir FockJohn Slater and George Koster
유형Electronic structure methodElectronic structure methodSimplified electronic structure model
원전Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138. DOI ↗Fock, V. (1930). Näherungsmethode zur Lösung des quantenmechanischen Mehrkörperproblems. Zeitschrift für Physik, 61, 126–148. link ↗Slater, J. C., Koster, G. F. (1954). Simplified LCAO method for the periodic potential problem. Physical Review, 94, 1498–1524. DOI ↗
별칭DFT, Kohn-Sham equationsHF, self-consistent fieldTB model, hopping model
관련443
요약Density 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.The Hartree-Fock (HF) method is a foundational self-consistent field approach for solving the many-electron Schrödinger equation. Developed independently by Douglas Hartree and Vladimir Fock in the late 1920s, it approximates the ground state by assuming electrons move in an average field generated by all other electrons, enabling tractable quantum chemistry calculations.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.
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ScholarGate방법 비교: Density Functional Theory · Hartree-Fock Method · Tight-Binding Model. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare