Speaker
Weiyan Zhang
(Hebei Normal University)
Description
The classification of cosmic-ray components in ground-based air shower experiments such as LHAASO is a challenging task. ParticleNet is a DGCNN-based model designed for particle physics applications. In this presentation, we use ParticleNet to identify the proton and light components from background cosmic-ray events in the simulation data of LHAASO-KM2A. The results show enhanced classification performance compared to the baseline method, demonstrating the promise of advanced deep learning techniques in cosmic-ray data analysis.
Primary authors
Weiyan Zhang
(Hebei Normal University)
Xiaopeng Zhang
(IHEP)
