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◆ Journal of Engineering2026-08-01· Glauber

Beyond the Optical Limit in p-18O Collisions: Glauber Model Calculations with Woods-Saxon and Sharp-Sphere Density Distributions

Israa Ali Madhi, Basim Khalaf Rejah

原始摘要(英文原文)· Original abstract
This study investigates high-energy proton–oxygen collisions (√sNN=0.056) using the Optical Glauber Model and accounts for how different nuclear density distributions affect the properties of the collision both geometrically and dynamically. The Glauber Model is a very common technique in heavy-ion physics that treats nuclei as continuous matter distributions; however, the effect on proton–nucleus systems of adopting different nuclear density distributions remains insufficiently studied, especially the Woods–Saxon and Sharp-Sphere distributions. In this regard, oxygen nuclei were selected because their low mass makes them an important reference system that has rarely been considered for comparison in the past. This work provides a systematic comparison of these two density distributions by computing several observables such as the thickness and overlap functions, the number of participating nucleons, and the number of binary collisions. It is observed from the results that the Woods–Saxon distribution produces a relatively smoother and wider overlap geometry along with a larger Npart, while the Sharp-Sphere distribution provides steeper behaviour to all observables as the collision impact parameter increases. In both cases, the Npart and the Ncoll decrease with a higher collision impact parameter, owing to a shrinking nuclear overlap region. These results demonstrate a significant sensitivity of the collision geometry on the presumed method of specifying the nuclear density distribution, as well as emphasize that precise models of nuclear structure are essential to describing properties of the initial state in high-energy p-18O interactions.
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Beyond the Optical Limit in p-18O Collisions: Glauber Model Calculations with Woods-Saxon and Sharp-Sphere Density Distributions — 科研速览 Science Skim