AI 中文总结
本文开发了可追溯两点关联信号至单个数据点贡献的算法，借此发现银河系普遍存在空间聚类、垂直密度波受复杂波动扭曲，还探索了厚盘与近晕恒星成团及结构定年的可能性。
AI 中文摘要
两点关联函数可用于证明数据集内子结构的存在，但常规实现方式不会追踪构成每个特定子结构的单个数据点。本文开发了一种算法，能将两点关联信号追溯至每个数据点的贡献，从而以新颖方式可视化结构。利用该工具，我们发现银河系中普遍存在空间聚类的大量证据，揭示了扭曲此前发现的垂直密度波的复杂波动；还探索了厚盘与近晕区域恒星的“成团”现象，并讨论了对该结构进行定年的可能性。
英文摘要
The Two-Point Correlation Function can be used to demonstrate the existence of substructure within a dataset, but typical implementations do not track the individual points which contribute to each specific substructure. In this paper, we develop an algorithm that traces a two-point correlation signal back to the contributions of each data point, allowing for structure to be visualized in novel ways. Using this tool, we find substantial evidence for pervasive spatial clustering in the Milky Way and reveal complex undulations that warp the previously discovered vertical density waves. We also explore the ``clumping" of stars in the thick disk and near-halo regions and discuss the possibility of dating the structure.
CommentsPublished in the Open Journal of Astrophysics
