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Register a new userBlue Straggler Populations of Seven Open Clusters with Gaia DR2
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Added by
Souradeep Bhattacharya
Publication date
2020
fields
Physics
and research's language is
English
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Blue straggler stars (BSS) are well studied in globular clusters but their systematic study with secure membership determination is lacking in open clusters. We use Gaia DR2 data to determine accurate stellar membership for four intermediate-age open clusters, Melotte 66, NGC 2158, NGC 2506 and NGC 6819, and three old open clusters, Berkeley 39, NGC 188 and NGC 6791, to subsequently study their BSS populations. The BSS radial distributions of five clusters, Melotte 66, NGC 188, NGC 2158, NGC 2506, and NGC 6791, show bimodal distributions, placing them with Family II globular clusters which are of intermediate dynamical ages. The location of minima, $r_mathrm{{min}}$, in the bimodal BSS radial distributions, varies from 1.5$r_c$ to 4.0$r_c$, where $r_c$ is the core radius of the clusters. We find a positive correlation between $r_mathrm{{min}}$ and $N_{mathrm{relax}}$, the ratio of cluster age to the current central relaxation time of the cluster. We further report that this correlation is consistent in its slope, within the errors, to the slope of the globular cluster correlation between the same quantities, but with a slightly higher intercept. This is the first example in open clusters that shows BSS radial distributions as efficient probes of dynamical age. The BSS radial distributions of the remaining two clusters, Berkeley 39 and NGC 6819, are flat. The estimated $N_{mathrm{relax}}$ values of these two clusters, however, indicate that they are dynamically evolved. Berkeley 39 especially has its entire BSS population completely segregated to the inner regions of the cluster.
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Blue straggler stars are exotic objects present in all stellar environments whose nature and formation channels are still partially unclear. They seem to be particularly abundant in open clusters (OCs), thus offering a unique chance to tackle these problems statistically.We aim to build up a new and homogeneous catalogue of blue straggler stars (BSS) in Galactic OCs using Gaia to provide a more solid assessment of the membership of these stars. We also aim to explore possible relationships of the straggler abundance with the parent clusters structural and dynamical parameters. As a by-product, we also search for possible yellow straggler stars (YSS), which are believed to be stragglers in a more advanced evolution stage. We employed photometry, proper motions, and parallaxes extracted from Gaia DR2 for 408 Galactic star clusters and searched for stragglers within them after performing a careful membership analysis. The number of BBS emerging from our more stringent, selection criteria turns out to be significantly smaller than in previo
Very precise observational data are needed for studying the stellar cluster parameters (distance, reddening, age, metallicity) and cluster internal kinematics. In turn, these give us an insight into the properties of our Galaxy, for example, by giving us the ability to trace Galactic spiral structure, star formation rates and metallicity gradients. We investigated the available Gaia DR2 catalogue of 1229 open clusters and studied cluster distances, sizes and membership distributions in the 3D space. An appropriate analysis of the parallaxto-distance transformation problem is presented in the context of getting distances toward open clusters and estimating their sizes. Based on our investigation of the Gaia DR2 data we argue that, within 2 kpc, the inverse-parallax method gives comparable results (distances and sizes) as the Bayesian approach based on the exponentially decreasing volume density prior. Both of these methods show very similar dependence of the line-of-sight elongation of clusters (needle-like shapes resulting from the parallax uncertainties) on the distance. We also looked at a measure of elongations of the studied clusters and find the maximum distance of 665 pc at which a spherical fit still contains about half of the stellar population of a cluster. It follows from these results that the 3D structure of an open cluster cannot be properly studied beyond about 500 pc when using any of mentioned standard transformations of parallaxes to distances.
The publication of the Gaia Data Release 2 (Gaia DR2) opens a new era in Astronomy. It includes precise astrometric data (positions, proper motions and parallaxes) for more than $1.3$ billion sources, mostly stars. To analyse such a vast amount of new data, the use of data mining techniques and machine learning algorithms are mandatory. The search for Open Clusters, groups of stars that were born and move together, located in the disk, is a great example for the application of these techniques. Our aim is to develop a method to automatically explore the data space, requiring minimal manual intervention. We explore the performance of a density based clustering algorithm, DBSCAN, to find clusters in the data together with a supervised learning method such as an Artificial Neural Network (ANN) to automatically distinguish between real Open Clusters and statistical clusters. The development and implementation of this method to a $5$-Dimensional space ($l$, $b$, $varpi$, $mu_{alpha^*}$, $mu_delta$) to the Tycho-Gaia Astrometric Solution (TGAS) data, and a posterior validation using Gaia DR2 data, lead to the proposal of a set of new nearby Open Clusters. We have developed a method to find OCs in astrometric data, designed to be applied to the full Gaia DR2 archive.
$Context$. 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 better understanding of the disc properties. $Aims$. The aim of the paper is to improve the knowledge of cluster parameters, using only the unprecedented quality of the Gaia photometry and astrometry. $Methods$. We make use of the membership determination based on the precise Gaia astrometry and photometry. We apply anautomated Bayesian tool, BASE-9, to fit stellar isochrones on the observed G, GBP, GRP magnitudes of the high probability member stars. $Results$. We derive parameters such as age, distance modulus and extinction for a sample of 269 open clusters, selecting only low reddening objects and discarding very young clusters, for which techniques other than isochrone-fitting are more suitable for estimating ages.
Blue straggler stars (BSSs) are the most massive stars in a cluster formed via binary or higher-order stellar interactions. Though the exact nature of such formation scenarios is difficult to pin down, we provide observational constraints on the different possible mechanism. In this quest, we first produce a catalogue of BSSs using Gaia DR2 data. Among the 670 clusters older than 300 Myr, we identified 868 BSSs in 228 clusters and 500 BSS candidates in 208 clusters. In general, all clusters older than 1 Gyr and massive than 1000 Msun have BSSs. The average number of BSSs increases with cluster age and mass, and there is a power-law relation between the cluster mass and the maximum number of BSSs in the cluster. We introduce the term fractional mass excess (Me) for BSSs. We find that at least 54% of BSSs have Me $<$ 0.5 (likely to have gained mass through a binary mass transfer (MT)), 30% in the $1.0 <$ Me $< 0.5$ range (likely to have gained mass through a merger) and up to 16% with Me $>$ 1.0 (likely from multiple mergers/MT). We also find that the percentage of low Me BSSs increases with age, beyond 1--2 Gyr, suggesting an increase in formation through MT in older clusters. The BSSs are radially segregated, and the extent of segregation depends on the dynamical relaxation of the cluster. The statistics and trends presented here are expected to constrain the BSS formation models in open clusters.
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