قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| مونت كارلو الكمومي× | نظرية الكثافة الوظيفية× | |
|---|---|---|
| المجال | الحوسبة الكمومية | الحوسبة الكمومية |
| العائلة | Machine learning | Machine learning |
| سنة النشأة≠ | 1953 | 1965 |
| صاحب الطريقة≠ | Nicholas Metropolis and colleagues | Walter Kohn |
| النوع≠ | Monte Carlo simulation | Electronic structure method |
| المصدر التأسيسي≠ | Metropolis, N., Rosenbluth, A. W., et al. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092. DOI ↗ | Kohn, W., Sham, L. J. (1965). Self-consistent equations including exchange and correlation effects. Physical Review, 140, A1133–A1138. DOI ↗ |
| الأسماء البديلة≠ | QMC, variational Monte Carlo, diffusion Monte Carlo | DFT, Kohn-Sham equations |
| ذات صلة≠ | 3 | 4 |
| الملخص≠ | 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. | 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. |
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