Сравнение на методи

	Профил на халото на Navarro-Frenk-White (NFW)	Метод на матричния елемент	Fitting на партонни разпределителни функции (PDF)
Област	Физика на елементарните частици	Физика на елементарните частици	Физика на елементарните частици
Семейство	Process / pipeline	Process / pipeline	Process / pipeline
Година на възникване	1997	1988	1969
Създател	Julio Navarro, Carlos Frenk, Simon White	K. Kondo	James Bjorken and collaborators
Тип	Halo density model	Probability calculation framework	QCD framework
Основополагащ източник	Navarro, J. F., Frenk, C. S., & White, S. D. M. (1997). A universal density profile from hierarchical clustering. The Astrophysical Journal, 490(2), 493.	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.	Bjorken, J. D. (1969). Asymptotic sum rules at infinite momentum. Physical Review, 179(5), 1547.
Други названия	NFW profile, dark matter density profile, halo model	MEM, matrix element calculation, amplitude evaluation	PDF, structure function, parton model
Свързани	3	3	3
Резюме	The Navarro-Frenk-White (NFW) profile is a widely-adopted density profile for dark matter halos emerging from cosmological simulations. It provides a simple parametric description of how dark matter density varies with distance from the halo center, essential for modeling galaxy cluster mass distributions, weak lensing, and dark matter annihilation signals.	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.	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.