Energy Reconstruction of LHAASO-KM2A with Machine Learning Methods

作者：Xiaopeng Zhang, Tian Xie, Jia Liu, Qingwen Tang, Sha Wu · 年份：2025 · DOI：10.22323/1.501.0451 · 研究领域：Distributed and Parallel Computing Systems

The measurement of high-energy cosmic ray spectra is important for understanding extreme astrophysical processes and the origins of cosmic rays, representing one of the core scientific objectives of the LHAASO-KM2A experiment. This study employs deep learning algorithms to directly extract event features from extensive raw data. Within the energy range of the "knee" region. This research employs ParticleNet, a graph-based neural network model that achieves markedly improved energy resolution and reduced bias compared to traditional parametric methods.