Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Подгонка PDF× | ВЕГАс Монте-Карло× | |
|---|---|---|
| Область | Физика элементарных частиц | Физика элементарных частиц |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1969 | 1978 |
| Автор метода≠ | James Bjorken and collaborators | Peter Lepage |
| Тип≠ | QCD framework | Adaptive sampling algorithm |
| Основополагающий источник≠ | Bjorken, J. D. (1969). Asymptotic sum rules at infinite momentum. Physical Review, 179(5), 1547. DOI ↗ | Lepage, G. P. (1978). A new algorithm for adaptive multidimensional integration. Journal of Computational Physics, 27(2), 192–203. DOI ↗ |
| Другие названия | PDF, structure function, parton model | VEGAS algorithm, adaptive importance sampling, multidimensional integration |
| Связанные | 3 | 3 |
| Сводка≠ | Parton Distribution Function (PDF) fitting is the process of determining the probability distributions of quarks and gluons inside hadrons using high-energy collision data. PDFs are fundamental inputs to all hadron collider phenomenology, essential for predicting cross-sections, designing triggers, and interpreting new physics searches at the Large Hadron Collider. | VEGAS is an adaptive Monte Carlo algorithm for numerical integration of multidimensional functions, particularly useful for high-dimensional integrals common in particle physics calculations. By adaptively refining the sampling distribution to concentrate points in high-contribution regions, VEGAS dramatically improves integration efficiency compared to naive Monte Carlo. |
| ScholarGateНабор данных ↗ |
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