AI 中文总结
研究高能宇宙射线各向异性测量问题，测试角功率谱和自相关函数方法，发现自相关函数在多数模型中最敏感，角功率谱在各向异性强时可提供额外知识，应用于KASCADE数据发现特定质量组在特定能量角尺度有各向异性迹象。
AI 中文摘要
我们研究了在所有角尺度上测量高能宇宙射线各向异性的问题。地面宇宙射线实验的视场有限且曝光不均匀，降低了其对宇宙射线到达方向真实各向异性的灵敏度。广泛使用的各向异性特征——赤经上通量展开的偶极子——对宇宙射线起源和传播的潜在物理机制了解非常有限。本研究测试了另外两种方法：角功率谱和自相关函数对宇宙射线通量可能的中、小尺度各向异性的灵敏度。我们发现，在大多数测试模型中，自相关函数是对潜在物理各向异性最敏感的估计器，而当各向异性足够强时，角功率谱可以提供有关宇宙射线通量特性的额外知识。作为对我们发现的检验，我们将这些方法应用于KASCADE实验公共数据的10%样本。即，我们考虑了所有粒子事件集以及由卷积神经网络分类的单个质量组集。我们发现，对于铁核质量组，在能量约为20 PeV时，角功率谱和自相关方法在约10°角尺度上均表明存在>2.5σ水平的各向异性。
英文摘要
We study the problem of measuring the anisotropy of high-energy cosmic rays across all angular scales. The limited field of view and non-uniform exposure of ground-based cosmic-ray experiments reduce their sensitivity to real anisotropy of cosmic-ray arrival directions. A widely used signature of anisotropy -- a dipole of the flux expansion over the right ascension -- provides very limited understanding of the underlying physics of cosmic-ray origin and propagation. In this study we test two other methods: the angular power spectrum and the autocorrelation function for sensitivity to possible medium- and small-scale anisotropies of cosmic-ray flux. We find that the autocorrelation function is the most sensitive estimator for an underlying physical anisotropy in most of the models tested, while the angular power spectrum can provide additional knowledge about cosmic-ray flux properties, when the anisotropy is strong enough. As a test of our findings, we apply these methods to $10\%$ sample of the KASCADE experiment public data. Namely, we consider all-particle set of events and sets of individual mass groups classified by a convolutional neural network. We find an indication of anisotropy at $> 2.5 σ$ level at $\sim 10^\circ$ angular scale for the iron nuclei mass group at $E \gtrsim 20$ PeV with both the angular power spectrum and the autocorrelation methods.
Comments22 pages, 17 figures
