论文标题
使用pyupmask和随机森林混合方法在Gaia EDR3中识别46个新的开放群集候选者
Identify 46 New Open Clusters Candidates In Gaia EDR3 Using pyUPMASK and Random Forest Hybrid Method
论文作者
论文摘要
开放式簇（OC）被认为是理解恒星进化论并验证恒星模型的示踪剂。在这项研究中，我们提出了一种识别OC的强大方法。 Pyupmask和RF的混合方法首先用于删除野外星星并确定更可靠的成员。然后使用基于基于GAIA DR2和EDR3的3714 OC样本构建的RF算法的识别模型应用于识别OC候选。在等温拟合，晚期恒星种群合成（ASP）模型拟合和视觉检查后获得OC候选。使用拟议的方法，我们重新审视了868名候选人，并由Gaia Edr3的朋友的算法将其共同集中。除了已经报告的开放群集外，我们专注于剩下的300名未知候选人。从高到低配合的质量，这些未透露的候选人分别分别分为A（59），B级（21）和C类（220）。结果，在视觉检查后，确定了A类和B类中46个新的可靠开放群集候选。
Open clusters (OCs) are regarded as tracers to understand stellar evolution theory and validate stellar models. In this study, we presented a robust approach to identifying OCs. A hybrid method of pyUPMASK and RF is first used to remove field stars and determine more reliable members. An identification model based on the RF algorithm built based on 3714 OC samples from Gaia DR2 and EDR3 is then applied to identify OC candidates. The OC candidates are obtained after isochrone fitting, the advanced stellar population synthesis (ASPS) model fitting, and visual inspection. Using the proposed approach, we revisited 868 candidates and preliminarily clustered them by the friends-of-friends algorithm in Gaia EDR3. Excluding the open clusters that have already been reported, we focused on the remaining 300 unknown candidates. From high to low fitting quality, these unrevealed candidates were further classified into Class A (59), Class B (21), and Class C (220), respectively. As a result, 46 new reliable open cluster candidates among classes A and B are identified after visual inspection.
