M. Raja , P. Hasan , Md. Mahmudunnobe , Md. Saifuddin , S.N. Hasan
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引用次数: 0
摘要
在本文中,我们基于盖亚DR3数据,应用机器学习聚类算法Density Based Spatial Clustering of Applications with Noise(DBSCAN)来研究12个疏散星团(NGC 2264、NGC 2682、NGC 2244、NGC 3293、NGC 6913、NGC 7142、IC 1805、NGC 6231、NGC 2243、NGC 6451、NGC 6005和NGC 6583)中恒星的成员资格。这些星团样本涵盖了各种参数,如年龄、金属性、距离、消光以及广阔的适当运动和视差参数空间。我们利用 DBSCAN 获得了可靠的星团成员,其暗度可达 G∼20 mag,而且还包括星团的外围区域。利用我们修订的成员列表,我们绘制了色-星等图,并利用ASteCA获得了样本的星团参数,并与星表值进行了比较。我们还通过 APOGEE 和 GALAH 的光谱数据验证了我们的成员样本。本文证明了 DBSCAN 在确定星团成员资格方面的有效性。
Membership determination in open clusters using the DBSCAN Clustering Algorithm
In this paper, we apply the machine learning clustering algorithm Density Based Spatial Clustering of Applications with Noise (DBSCAN) to study the membership of stars in twelve open clusters (NGC 2264, NGC 2682, NGC 2244, NGC 3293, NGC 6913, NGC 7142, IC 1805, NGC 6231, NGC 2243, NGC 6451, NGC 6005 and NGC 6583) based on Gaia DR3 Data. This sample of clusters spans a variety of parameters like age, metallicity, distance, extinction and a wide parameter space in proper motions and parallaxes. We obtain reliable cluster members using DBSCAN as faint as mag and also in the outer regions of clusters. With our revised membership list, we plot color-magnitude diagrams and we obtain cluster parameters for our sample using ASteCA and compare it with the catalog values. We also validate our membership sample by spectroscopic data from APOGEE and GALAH for the available data. This paper demonstrates the effectiveness of DBSCAN in membership determination of clusters.
Astronomy and ComputingASTRONOMY & ASTROPHYSICSCOMPUTER SCIENCE,-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.10
自引率
8.00%
发文量
67
期刊介绍:
Astronomy and Computing is a peer-reviewed journal that focuses on the broad area between astronomy, computer science and information technology. The journal aims to publish the work of scientists and (software) engineers in all aspects of astronomical computing, including the collection, analysis, reduction, visualisation, preservation and dissemination of data, and the development of astronomical software and simulations. The journal covers applications for academic computer science techniques to astronomy, as well as novel applications of information technologies within astronomy.