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部分子分布函数(PDF)拟合×重整化群方程×Vegas Monte Carlo×
领域粒子物理学粒子物理学粒子物理学
方法族Process / pipelineProcess / pipelineProcess / pipeline
起源年份196919701978
提出者James Bjorken and collaboratorsCurtis Callan and David GrossPeter Lepage
类型QCD frameworkScale dependence frameworkAdaptive sampling algorithm
开创性文献Bjorken, J. D. (1969). Asymptotic sum rules at infinite momentum. Physical Review, 179(5), 1547. DOI ↗Callan, C. G. (1970). Broken scale invariance in scalar field theory. Physical Review D, 2(6), 1541. DOI ↗Lepage, G. P. (1978). A new algorithm for adaptive multidimensional integration. Journal of Computational Physics, 27(2), 192–203. DOI ↗
别名PDF, structure function, parton modelRGE, running couplings, beta function evolutionVEGAS algorithm, adaptive importance sampling, multidimensional integration
相关333
摘要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.Renormalization Group Equations (RGEs) describe how the coupling constants and masses of a quantum field theory evolve with energy scale. They are fundamental tools for understanding the scale dependence of physics, predicting the behavior of coupling strengths at different energies, and connecting high-energy physics to low-energy precision measurements.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.
ScholarGate数据集
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ScholarGate方法对比: PDF Fitting · Renormalization Group Equations · Vegas Monte Carlo. 于 2026-06-19 检索自 https://scholargate.app/zh/compare