sOPTICS: 一种用于识别星系群/星系团及最亮团星系的改进型密度聚类算法
sOPTICS: A Modified Density-Based Algorithm for Identifying Galaxy Groups/Clusters and Brightest Cluster Galaxies
AI总结：
本研究提出改进型密度聚类算法sOPTICS，通过引入缩放因子修正红移空间畸变导致的视线误差，在星系团及最亮团星系识别任务中准确率、纯度和回收率均优于传统FoF算法，且鲁棒性和灵活性强，适用于大规模天文巡天。
摘要：
研究星系与暗物质晕关联的一种直接方法是分析示踪潜在暗物质晕的星系群与星系团，这凸显了识别星系团及其关联的最亮团星系（BCGs）的重要性。在本研究中，我们测试并提出了一种鲁棒的密度聚类算法，在现有已发布的星系群/星系团星表中，其表现优于传统的Friends-of-Friends（FoF，朋友-朋友）算法。我们的新方法是Ordering Points To Identify the Clustering Structure（OPTICS，排序点识别聚类结构）算法的改进版本，它通过引入一个缩放因子来处理由红移空间畸变导致的视线位置不确定性，因此被称为sOPTICS。在基于半解析星系形成模拟的星系群星表和观测数据上进行测试时，我们的算法展现出对异常值的鲁棒性，且对超参数选择相对不敏感。我们总共对比了八种聚类算法的结果。所提出的密度聚类方法sOPTICS在不同环境中准确识别大质量星系团及其关联BCG方面的表现优于FoF，具有更高的纯度和回收率，还能在一个大型星系样本的118个可靠BCG中成功识别出115个。此外，在无需大量重新调参的情况下应用于独立观测星表时，sOPTICS仍保持高恢复效率，证实了其在大规模天文巡天中的灵活性与有效性。
英文摘要：
A direct approach to studying the galaxy-halo connection is to analyze groups and clusters of galaxies that trace the underlying dark matter halos, emphasizing the importance of identifying galaxy clusters and their associated brightest cluster galaxies (BCGs). In this work, we test and propose a robust density-based clustering algorithm that outperforms the traditional Friends-of-Friends (FoF) algorithm in the currently available galaxy group/cluster catalogs. Our new approach is a modified version of the Ordering Points To Identify the Clustering Structure (OPTICS) algorithm, which accounts for line-of-sight positional uncertainties due to redshift space distortions by incorporating a scaling factor, and is thereby referred to as sOPTICS. When tested on both a galaxy group catalog based on semi-analytic galaxy formation simulations and observational data, our algorithm demonstrated robustness to outliers and relative insensitivity to hyperparameter choices. In total, we compared the results of eight clustering algorithms. The proposed density-based clustering method, sOPTICS, outperforms FoF in accurately identifying giant galaxy clusters and their associated BCGs in various environments with higher purity and recovery rate, also successfully recovering 115 BCGs out of 118 reliable BCGs from a large galaxy sample. Furthermore, when applied to an independent observational catalog without extensive re-tuning, sOPTICS maintains high recovery efficiency, confirming its flexibility and effectiveness for large-scale astronomical surveys.
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