Classifier for centrality determination with zero-degree calorimeter at the cooling-storage-ring external-target experiment

作者：Zhang, Biao; Liu, Li-Ke; Pei, Hua; Shi, Shu-Su; Xu, Nu; Wang, Ya-Ping^*

来源：Nuclear Science and Techniques, 2023, 34(11): 176.

DOI：10.1007/s41365-023-01338-5

• ZDC
• Boosted decision trees
• Multi-classification
• IQMD
• Centrality determination

The zero-degree calorimeter (ZDC) plays a crucial role toward determining the centrality in the Cooling-Storage-Ring External-target Experiment (CEE) at the Heavy Ion Research Facility in Lanzhou. A boosted decision tree (BDT) multi-classification algorithm was employed to classify the centrality of the collision events based on the raw features from ZDC such as the number of fired channels and deposited energy. The data from simulated U-238 + U-238 collisions at 500 MeV/u, generated by the IQMD event generator and subsequently modeled using the GEANT4 package, were employed to train and test the BDT model. The results showed the high accuracy of the multi-classification model adopted in ZDC for centrality determination, which is robust against variations in different factors of detector geometry and response. This study demonstrates the good performance of CEE-ZDC in determining the centrality in nucleus-nucleus collisions.