Comparar métodos

	Eigensolver Cuántico Variacional	Teoría del Funcional de la Densidad
Campo	Computación cuántica	Computación cuántica
Familia	Machine learning	Machine learning
Año de origen	2014	1965
Autor original	Alberto Peruzzo	Walter Kohn
Tipo	Hybrid quantum-classical algorithm	Electronic structure method
Fuente seminal	Peruzzo, A., McClean, J., Shadbolt, P., et al. (2014). A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5, 4213.	Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138.
Alias	VQE, hybrid quantum-classical	DFT, Kohn-Sham equations
Relacionados	4	4
Resumen	The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm designed to find the lowest eigenvalue (ground state energy) of a quantum Hamiltonian. Introduced by Peruzzo et al. in 2014, it exploits the variational principle to combine the power of quantum circuits with classical optimization to solve chemistry and materials science problems on near-term quantum devices.	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.