论文标题
银河光环的层次结构：晕光的分类和表征
The Hierarchical Structure of Galactic Haloes: Classification and characterisation with Halo-OPTICS
论文作者
论文摘要
我们建立在订购点上以识别聚类结构（光学），这是一种众所周知的层次聚类算法，是一种可靠的数据钻机，以产生晕孔镜头，这是一种算法，该算法旨在自动检测和提取所有有意义的两个任意尺寸之间的所有有意义的群集。然后，我们将光环触发物应用于四个单独的合成银河系类型星系中光环颗粒的3D空间位置，从而对恒星和暗物质结构层次结构进行分类。通过可视化光晕输出，我们将其结构识别与最先进的星系/（子）光环查找器Velociraptor进行了比较，即使晕光镜在此当前实现中也不考虑运动学信息，也找到了出色的一致性。我们得出的结论是，晕光是一种强大的分层光环查找器，尽管它可以通过将额外的局部信息（例如粒子运动学和恒星金属性）纳入其距离指标，但可以改善较低的空间密度特征（例如溪流的尾巴）。
We build upon Ordering Points To Identify Clustering Structure (OPTICS), a hierarchical clustering algorithm well-known to be a robust data-miner, in order to produce Halo-OPTICS, an algorithm designed for the automatic detection and extraction of all meaningful clusters between any two arbitrary sizes. We then apply Halo-OPTICS to the 3D spatial positions of halo particles within four separate synthetic Milky Way type galaxies, classifying the stellar and dark matter structural hierarchies. Through visualisation of the Halo-OPTICS output, we compare its structure identification to the state-of-the-art galaxy/(sub)halo finder VELOCIraptor, finding excellent agreement even though Halo-OPTICS does not consider kinematic information in this current implementation. We conclude that Halo-OPTICS is a robust hierarchical halo finder, although its determination of lower spatial-density features such as the tails of streams could be improved with the inclusion of extra localised information such as particle kinematics and stellar metallicity into its distance metric.
