用DBSCAN进行化学盲标记：光谱测量的前景
Blind chemical tagging with DBSCAN: prospects for spectroscopic surveys
摘要：
化学标记作为一种揭开银河系历史的技术，有很大的希望。基于类似化学性质的恒星可以建立银河系恒星形成和合并历史的细节。通过对恒星化学的精确测量，化学标记可能能够将来自同一气体云的恒星分组在一起，而不管它们目前的位置和运动学如何。成功地标记这些出生集群需要高质量的化学空间信息和良好的集群发现算法。为了测试当前和即将到来的光谱调查数据的化学标记的可行性，我们构建了一组现实的合成集群，为每个恒星创建观察到的光谱和衍生的化学丰度。我们使用基于密度的空间聚类的应用程序与噪声（DBSCAN）分组恒星的光谱或丰度的基础上，这些组匹配到输入集群，并被发现是高度均匀和完整的。超过10个成员回收的集群的百分比是40%时，标记丰度与目前的技术实现的不确定性。基于我们的银河系的基准模型，我们预测恢复超过600个集群，至少有10个观察到的成员和70%的成员均匀性在一个类似于APOGEE调查的样本。在SDSS V中标记更大的调查，如GALAH调查和未来的银河系映射器，可以恢复数万个高度均匀的星系团。获得如此多独特的同生星团将改变我们对银河系恒星形成历史和化学演化的理解。
英文摘要：
Chemical tagging has great promise as a technique to unveil our Galaxy's history. Grouping stars based on their similar chemistry can establish details of the star formation and merger history of the Milky Way. With precise measurements of stellar chemistry, chemical tagging may be able to group together stars born from the same gas cloud, regardless of their current positions and kinematics. Successfully tagging these birth clusters requires high quality chemical space information and a good cluster-finding algorithm. To test the feasibility of chemical tagging on data from current and upcoming spectroscopic surveys, we construct a realistic set of synthetic clusters, creating both observed spectra and derived chemical abundances for each star. We use Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to group stars based on their spectra or abundances; these groups are matched to input clusters and are found to be highly homogeneous and complete. The percentage of clusters with more than 10 members recovered is 40% when tagging on abundances with uncertainties achievable with current techniques. Based on our fiducial model for the Milky Way, we predict recovering over 600 clusters with at least 10 observed members and 70% membership homogeneity in a sample similar to the APOGEE survey. Tagging larger surveys like the GALAH survey and the future Milky Way Mapper in SDSS V could recover tens of thousands of clusters at high homogeneity. Access to so many unique co-eval clusters will transform how we understand the star formation history and chemical evolution of our Galaxy.
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