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PDF 피팅×Matrix Element Method×베이거스 몬테카를로×
분야입자물리학입자물리학입자물리학
계열Process / pipelineProcess / pipelineProcess / pipeline
기원 연도196919881978
창시자James Bjorken and collaboratorsK. KondoPeter Lepage
유형QCD frameworkProbability calculation frameworkAdaptive sampling algorithm
원전Bjorken, J. D. (1969). Asymptotic sum rules at infinite momentum. Physical Review, 179(5), 1547. DOI ↗Kondo, K. (1988). Dynamical likelihood method for reconstruction of events produced by the top-quark pair in the lepton + jets channel at hadron colliders. Journal of the Physical Society of Japan, 57(12), 4126–4140. link ↗Lepage, G. P. (1978). A new algorithm for adaptive multidimensional integration. Journal of Computational Physics, 27(2), 192–203. DOI ↗
별칭PDF, structure function, parton modelMEM, matrix element calculation, amplitude evaluationVEGAS algorithm, adaptive importance sampling, multidimensional integration
관련333
요약Parton 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.The Matrix Element Method (MEM) is a powerful analysis technique that leverages quantum field theory amplitudes to extract maximum physics information from individual events. By comparing observed detector signatures to predictions from matrix elements, MEM provides unbiased, model-independent measurements with excellent theoretical precision and sensitivity to new physics.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.
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