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| Метод на Хартри-Фок× | Квантов Монте Карло× | |
|---|---|---|
| Област | Квантови изчисления | Квантови изчисления |
| Семейство | Machine learning | Machine learning |
| Година на възникване≠ | 1928 | 1953 |
| Създател≠ | Douglas Hartree and Vladimir Fock | Nicholas Metropolis and colleagues |
| Тип≠ | Electronic structure method | Monte Carlo simulation |
| Основополагащ източник≠ | Fock, V. (1930). Näherungsmethode zur Lösung des quantenmechanischen Mehrkörperproblems. Zeitschrift für Physik, 61, 126–148. link ↗ | Metropolis, N., Rosenbluth, A. W., et al. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092. DOI ↗ |
| Други названия≠ | HF, self-consistent field | QMC, variational Monte Carlo, diffusion Monte Carlo |
| Свързани≠ | 4 | 3 |
| Резюме≠ | 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. | 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. |
| ScholarGateНабор от данни ↗ |
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