用多尺度分析方法分辨“膝”区原初宇宙线中的铁核成分

基于对ARGO-YBJ实验进行的Monte Carlo模拟计算,利用多重分形和离散小波方法在不同尺度下对“膝”区原初宇宙线粒子所产生的广延空气簇射中的次级粒子的横向分布特征进行了分析,得到了多个可以表征不同原初之间差异的参量,以这些参量作为人工神经网络的输入进行了多参量分析,并研究了该网络对原初粒子的分辨能力。

Multi-scale image analysis applied to distinguish primary iron of cosmic rays in the knee region

Based on the Monte Carlo simulation for ARGO-YBJ experiment, the characteristics of lateral distribution of the charged particles in Extensive Air Showers induced by primary cosmic ray particles with energy at the “knee” region were analyzed by using the multi-fractal and discrete wavelet methods under different length scales. Parameters, which can characterize the difference between different primary particles, were found. With these parameters as the inputs, an artificial neural network was created for multi-variant analysis, and the discrimination power was given.