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