4 papers
Bayesian extraction of TMC-free collectivity in p+p and p+Pb collisions at the LHC
Shuang Guo, Jia-Lin Pei, Guo-Liang Ma +1
A central challenge in understanding the origin of collective flow-like signatures in small collision systems calls for a reliable method to disentangle genuine collective flow fro…
Neural Unfolding of the Chiral Magnetic Effect in Heavy-Ion Collisions
Shuang Guo, Lingxiao Wang, Kai Zhou +1
The search for the chiral magnetic effect (CME) in relativistic heavy-ion collisions (HICs) is challenged by significant background contamination. We present a novel deep learning…
Latent Representation Learning in Heavy-Ion Collisions with MaskPoint Transformer
Jing-Zong Zhang, Shuang Guo, Li-Lin Zhu +2
A central challenge in high-energy nuclear physics is to extract informative features from the high-dimensional final-state data of heavy-ion collisions (HIC) in order to enable re…
Machine learning study to identify collective flow in small and large colliding systems
Shuang Guo, Han-Sheng Wang, Kai Zhou +1
Collective flow has been found to be similar between small colliding systems ( and A collisions) and large colliding systems (peripheral A A collisions) at t…