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	Metodo KKR	Teoria del Funzionale Densità	Metodo di Hartree-Fock
Campo	Calcolo quantistico	Calcolo quantistico	Calcolo quantistico
Famiglia	Machine learning	Machine learning	Machine learning
Anno di origine	1947	1965	1928
Ideatore	Joop Korringa and Walter Kohn	Walter Kohn	Douglas Hartree and Vladimir Fock
Tipo	Electronic structure method	Electronic structure method	Electronic structure method
Fonte seminale	Korringa, J. (1947). On the calculation of the energy of a Bloch wave in a metal. Physica, 13, 392–400.	Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138.	Fock, V. (1930). Näherungsmethode zur Lösung des quantenmechanischen Mehrkörperproblems. Zeitschrift für Physik, 61, 126–148.
Alias	KKR, multiple scattering	DFT, Kohn-Sham equations	HF, self-consistent field
Correlati	3	4	4
Sintesi	The Korringa-Kohn-Rostoker (KKR) method is a powerful multiple-scattering approach for calculating electronic band structures and properties of periodic and disordered solids. Developed in the late 1940s, KKR treats electrons as scattering from atomic potentials in a muffin-tin geometry, enabling efficient calculations for both crystalline and amorphous systems.	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.	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.