পদ্ধতির তুলনা করুন

	ভ্যারিয়েশনাল কোয়ান্টাম আইগেনসলভার	ঘনত্ব কার্যকরী তত্ত্ব
ক্ষেত্র	কোয়ান্টাম কম্পিউটিং	কোয়ান্টাম কম্পিউটিং
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	2014	1965
প্রবর্তক	Alberto Peruzzo	Walter Kohn
ধরন	Hybrid quantum-classical algorithm	Electronic structure method
মৌলিক উৎস	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.
অপর নাম	VQE, hybrid quantum-classical	DFT, Kohn-Sham equations
সম্পর্কিত	4	4
সারসংক্ষেপ	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.