arXiv 2108.027832021-08-05astro-ph.GA

用极端去卷积高斯混合模型计算Gaia DR2中431个疏散星团的成员名单

Membership lists for 431 open clusters in Gaia DR2 using extreme deconvolution gaussian mixture models

Karl Jaehnig, Jonathan Bird, Kelly Holley-Bockelmann

备注：: Accepted for publication in ApJ. Contains 26 pages, 11 figures, 2 tables, full tables will be available via CDS at a later time
DOI：: 10.3847/1538-4357/ac1d51

摘要：

疏散星团是同时形成的恒星群，使它们成为测试恒星形成理论、恒星演化和银河系圆盘动力学的理想实验室。然而，一个疏散星团的效用可能会受到其已知成员的准确性和完整性的限制。在这里，我们采用了“自上而下”的技术，{ \it极端反卷积高斯混合模型}（XDGMM），提取和评估已知的疏散星团从盖亚DR 2拟合恒星视差和自行的分布沿视线。极端反卷积技术可以恢复天体测量量的内在分布，占全部协方差矩阵的错误，这使得疏散星团成员被确定，即使在相对不确定的测量数据。到目前为止，疏散星团的研究只适用于极端反卷积专门搜索个别系统。我们使用XDGMM来表征Ahumada等人2007年报道的疏散星团，并能够恢复其中426个疏散星团中的420个（98.1\%）。我们的成员列表包含绝大多数（$>95\%$）以前已知的集群成员。我们还确定了一个新的，重要的，相对较弱的集群成员人口，并验证其成员身份使用盖亚eDR 3。我们报告在我们分析的视线范围内偶然发现了11个新的疏散星团候选者。我们提出了我们的技术，它的优点和挑战，以及公布我们的成员名单和更新的集群参数。

英文摘要：

Open clusters are groups of stars that form at the same time, making them an ideal laboratory to test theories of star formation, stellar evolution, and dynamics in the Milky Way disk. However, the utility of an open cluster can be limited by the accuracy and completeness of its known members. Here, we employ a "top-down" technique, {\it extreme deconvolution gaussian mixture models} (XDGMM), to extract and evaluate known open clusters from Gaia DR2 by fitting the distribution of stellar parallax and proper motion along a line-of-sight. Extreme deconvolution techniques can recover the intrinsic distribution of astrometric quantities, accounting for the full covariance matrix of the errors; this allows open cluster members to be identified even when presented with relatively uncertain measurement data. To date, open cluster studies have only applied extreme deconvolution to specialized searches for individual systems. We use XDGMM to characterize the open clusters reported by Ahumada et al. 2007 and are able to recover 420 of the 426 open clusters therein (98.1\%). Our membership list contains the overwhelming majority ($>95\%$) of previously known cluster members. We also identify a new, significant, and relatively faint cluster member population and validate their membership status using Gaia eDR3. We report the fortuitous discovery of 11 new open cluster candidates within the lines of sight we analyzed. We present our technique, its advantages and challenges, as well as publish our membership lists and updated cluster parameters.

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