arXiv:2401.06895·v2·Data Analysis, Statistics and Probability
Mini-jet Clustering Algorithm Using Transverse-momentum Seeds in High-energy Nuclear Collisions
Hanpu Jiang🇺🇸 · Nanxi Yao🇺🇸 · Cheuk-Yin Wong🇺🇸 · Gang Wang🇺🇸 · Huan Zhong Huang🇺🇸
Abstract
We propose an algorithm to detect mini-jet clusters in high-energy nuclear collisions, by selecting a high-transverse-momentum () particle as a seed and assigning a clustering radius () in the pseudorapidity and azimuthal-angle space. Our PYTHIA simulations for + collisions show that a scheme with a seeding of around 0.5 GeV/ and of approximately 0.6 satisfactorily identifies mini-jet clusters. The correlation between clusters obtained in PYTHIA calculations using the algorithm exhibits the proper behavior of hard-scattering-like processes, suggesting its usefulness in isolating mini-jet-like clusters from non-hard-scattering soft processes when applied to actual nuclear-collision data, thereby allowing a closer examination of both the mini-jet and the soft mechanisms.
Comments: 12 pages, 13 figures