1. A machine learning study to identify collective flow in small and large colliding systems
- Author
-
Wang, Han-Sheng, Guo, Shuang, Zhou, Kai, and Ma, Guo-Liang
- Subjects
Nuclear Theory (nucl-th) ,High Energy Physics - Phenomenology ,High Energy Physics - Phenomenology (hep-ph) ,Nuclear Theory ,FOS: Physical sciences ,Nuclear Experiment (nucl-ex) ,Nuclear Experiment - Abstract
Collective flow has been found similar between small colliding systems (p+p and p+A collisions) and large colliding systems (peripheral A+A collisions) at the CERN Large Hadron Collider (LHC). In order to study the difference of collective flow between small and large colliding systems, we employ a point cloud network to identify $p$ $+$ Pb collisions and peripheral Pb $+$ Pb collisions at $\sqrt{s_{NN}} =$ 5.02 TeV from a multiphase transport model (AMPT). After removing the discrepancies in the pseudorapidity distribution and the $p_{\rm T}$ spectra, we capture the discrepancy in anisotropic flow. Although the verification accuracy of our PCN is limited due to similar event-by-event distributions of elliptic and triangular flow, we demonstrate that collective flow between $p$ $+$ Pb collisions and peripheral Pb $+$ Pb collisions becomes more different with increasing final hadron multiplicity and parton scattering cross section., 9 pages, 11 figures
- Published
- 2023