4.7 Article

Event-by-event investigation of the two-particle source function in √sNN=2.76 TeV PbPb collisions with EPOS

期刊

PHYSICS LETTERS B
卷 847, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.physletb.2023.138295

关键词

-

向作者/读者索取更多资源

This study presents the investigation of the two-particle source function in lead-lead collisions simulated by the EPOS model. The results show that a Levy source shape, deviating significantly from a Gaussian shape, is observed for pions, kaons, and protons in individual events. The source parameters extracted are found to be related to the collision centrality and pair average transverse mass. Furthermore, the effects of decay products on the Levy exponent are studied, showing a decrease when including decay products, and no mT-scaling is found across different particle species.
The investigation of the two-particle source function in lead-lead collisions simulated by the EPOS model at a center of mass energy per nucleon pair of root sNN = 2.76 TeV is presented. The two-particle source functions are reconstructed directly on an event-by-event basis for pions, kaons and protons separately, using the final stage of EPOS. A Levy source shape is observed for all three particle species in the individual events, deviating significantly from a Gaussian shape. The source parameters are extracted as functions of collision centrality and pair average transverse mass (mT). The Levy exponent is found to be ordered accordingly to particle mass. The Levy scale parameter is found to scale for all particle species with mT according to Gaussian hydrodynamic predictions; however, there is no mT-scaling found across these species. In case of pions, the effects of the decay products and hadronic rescattering are also investigated. The Levy exponent is decreased when decay products are also included in the analysis. Without hadronic rescattering and decay products, the source shape is close to a Gaussian.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据