标题： 通过PCA研究膝区宇宙射线质量组成 显示英文标题

标题： Cosmic Ray Mass Composition Around the Knee via PCA

摘要： 在本文中，我们将主成分分析（PCA）应用于KASCADE实验记录的实验数据，以重建围绕\textit{膝盖}区域宇宙射线的质量组成。 考虑了一组对初级粒子质量敏感的四个广延大气簇射参数（$LCm$、$N_{\mu}$、$N_{e}$和横向簇射$age$），其坐标被转换为一个新的正交基，该基能够最大程度地捕捉数据方差。 基于前两个主成分（PCA0 对 PCA1）的实验分布以及考虑到五种类型初级粒子（p、He、C、Si 和 Fe）和三种强子相互作用模型（EPOS-LHC、QGSjet-II-04 和 SIBYLL~2.3d）的KASCADE阵列完整蒙特卡罗模拟，我们得到了每种初级粒子丰度随能量的变化，以及平均对数质量随能量的变化。 我们发现，通过这种综合分析得到的质量组成重建显著减少了对模拟过程中使用的强子相互作用模型的依赖，尽管初始输入参数是模型相关的。 此外，结果支持这样一个观点：在\textit{膝盖}区域附近，轻组分（质子）的丰度减少，而重组分则略有增加。 从该分析得出的$\langle \ln A \rangle$随能量变化的演变与LHAASO--KM2A实验的最新结果高度一致，并与数据驱动的GSF天体物理模型的预测非常吻合。 显示英文摘要

摘要： In this paper, we apply Principal Component Analysis (PCA) to experimental data recorded by the KASCADE experiment to reconstruct the mass composition of cosmic rays around the \textit{knee} region. A set of four extensive air shower parameters sensitive to the primary particle mass ($LCm$, $N_{\mu}$, $N_{e}$, and lateral shower $age$) was considered, whose coordinates were transformed into a new orthogonal basis that maximally captures the data variance. Based on the experimental distributions of the first two principal components (PCA0 vs.\ PCA1) and full Monte Carlo simulations of the KASCADE array considering five types of primary particles (p, He, C, Si, and Fe) and three hadronic interaction models (EPOS-LHC, QGSjet-II-04, and SIBYLL~2.3d), we obtained the evolution of the abundance of each primary species as a function of energy, as well as the evolution of the mean logarithmic mass with energy. We found that the reconstruction of the mass composition resulting from this comprehensive analysis significantly reduces dependence on the hadronic interaction model used in the simulation process, even though the initial input parameters are model-dependent. Moreover, the results support the idea that around the \textit{knee} region, the abundance of the light component (protons) decreases, while the heavy component shows a slight increase. The evolution of $\langle \ln A \rangle$ as a function of energy derived from this analysis shows excellent agreement with recent results from the LHAASO--KM2A experiment and aligns very well with the predictions of the data-driven GSF astrophysical model.