相关论文: A machine learning-based tool for open cluster mem…
We present a novel approach for identifying members of open star clusters using Gaia DR3 data by combining Minimum Spanning Tree (MST) and Gaussian Mixture Model (GMM) techniques. Our method employs a three-step process: initial filtering…
Membership of stars in open clusters is one of the most crucial parameters in studies of star clusters. Gaia opened a new window in the estimation of membership because of its unprecedented 6-D data. In the present study, we used published…
Star clusters are interesting laboratories to study star formation, single and binary stellar evolution, and stellar dynamics. We have used the exquisite data from $Gaia$'s data release 3 (DR3) to study 21 relatively rich and nearby open…
Open clusters are among the most useful and widespread tracers of Galactic structure. The completeness of the Galactic open cluster census, however, remains poorly understood. For the first time ever, we establish the selection function of…
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…
Context. Since the first publication of the Gaia catalogue a new view of our Galaxy has arrived. Its astrometric and photometric information has improved the precision of the physical parameters of open star clusters obtained from them.…
Open clusters are convenient probes of the structure and history of the Galactic disk. They are also fundamental to stellar evolution studies. The second Gaia data release contains precise astrometry at the sub-milliarcsecond level and…
In our previous work, we introduced a method that combines two unsupervised algorithms: DBSCAN and GMM. We applied this method to 12 open clusters based on Gaia EDR3 data, demonstrating its effectiveness in identifying reliable cluster…
The existing open cluster membership determination algorithms are either prior dependent on some known parameters of clusters or are not automatable to large samples of clusters. In this paper, we present, ML-MOC, a new machine learning…
In Gaia DR2, the unprecedented high-precision level reached in sub-mas for astrometry and mmag for photometry. Using cluster members identified with these astrometry and photometry in Gaia DR2, we can obtain a reliable determination of…
$Context$. Gaia Second Data Release provides precise astrometry and photometry for more than 1.3 billion sources. This catalog opens a new era concerning the characterization of open clusters and test stellar models, paving the way for a…
Open clusters have long been used to gain insights into the structure, composition, and evolution of the Galaxy. With the large amount of stellar data available for many clusters in the Gaia era, new techniques must be developed for…
Reliable fundamental parameters of open clusters such as distance, age and extinction are key to our understanding of Galactic structure and stellar evolution. In this work we use {\it Gaia} DR2 to investigate 45 open clusters listed in the…
The Gaia Data Release 2 (DR2) provided an unprecedented volume of precise astrometric and excellent photometric data. In terms of data mining the Gaia catalogue, machine learning methods have shown to be a powerful tool, for instance in the…
Context. Near open clusters as Pleiades, Praesepe and Blanco 1 have been extensively studied due to their proximity to the Sun. The Gaia data brings the opportunity to investigate these clusters, since it contains valuable astrometric and…
The third Gaia data release (DR3) contains $\sim$170\,000 astrometric orbit solutions of two-body systems located within $\sim$500 pc of the Sun. Determining component masses in these systems, in particular of stars hosting exoplanets,…
Data from the Gaia satellite are revolutionising our understanding of the Milky Way. With every new data release, there is a need to update the census of open clusters. We aim to conduct a blind, all-sky search for open clusters using 729…
The unprecedented precision of Gaia has led to a paradigm shift in membership determination of open clusters where a variety of machine learning (ML) models can be employed. In this paper, we apply the unsupervised Gaussian Mixture Model…
We report 541 new open cluster candidates in Gaia EDR3 through revisiting the cluster results from an earlier analysis of the Gaia DR2, which revealed nearly a thousand open cluster candidates in the solar neighborhood (mostly d < 3 kpc)…
Membership analysis is an important tool for studying star clusters. There are various approaches to membership determination, including supervised and unsupervised machine learning (ML) methods. We perform membership analysis using the…