Bandingkan kaedah

	Teori Fungsian Ketumpatan	Kuantum Monte Carlo
Bidang	Perkomputeran Kuantum	Perkomputeran Kuantum
Keluarga	Machine learning	Machine learning
Tahun asal	1965	1953
Pengasas	Walter Kohn	Nicholas Metropolis and colleagues
Jenis	Electronic structure method	Monte Carlo simulation
Sumber perintis	Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138.	Metropolis, N., Rosenbluth, A. W., et al. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092.
Alias	DFT, Kohn-Sham equations	QMC, variational Monte Carlo, diffusion Monte Carlo
Berkaitan	4	3
Ringkasan	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.	Quantum Monte Carlo (QMC) is a stochastic computational method for computing ground state properties of quantum many-body systems. Combining classical Monte Carlo sampling with quantum mechanics, QMC approaches are among the most accurate methods available for electronic structure and condensed matter physics, achieving sub-percent accuracy for many systems.