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Register a new userSearch for the evolutionary relationship between Galactic globular and open clusters using data from the Gaia DR2 Catalog
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Passing through the Galactic disk, a massive object such as a globular cluster, can trigger star formation process leading to the birth of open clusters. Here, we analyze such possible evolutionary relationship between globular and open clusters. To search for the closest rapprochement between objects we computed backwards the orbits of 150 Galactic globular and 232 open clusters (younger than 100 Myr) with proper motions, derived from the Gaia DR2 Catalog. The orbits were computed using the recently modified three-component (disk, bulge and halo) axisymmetric Navarro-Frenk-White potential, which was complemented by non-axisymmetric bar and spiral density wave potentials. We obtained a new estimate for the frequency of impacts of globular clusters about the Galactic disk, which is equal to 4 events for 1 million years. In the framework of the considered scenario, we highlight the following nine pairs of globular and open clusters, with rapprochement within 1 kpc at the time of the intersection the Galactic disk by a globular cluster for the latest 100 Myr: NGC 104 - Turner 3, NGC 104 - NGC 6396, NGC 104 - Ruprecht 127, NGC 5139 - Trumpler 17, NGC 5139 - NGC 6520, NGC 6341 - NGC 6613, NGC 6838 - NGC 6520, NGC 7078 - NGC 7063, NGC 6760 - Ruprecht 127.
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We employ Gaia DR2 proper motions for 151 Milky Way globular clusters from Vasiliev (2019) in tandem with distances and line-of-sight velocities to derive their kinematical properties. To assign clusters to the Milky Way thick disk, bulge, and halo we follow the approach of Posti et al. (2018) who distinguished among different Galactic stellar components using starss orbits. In particular, we use the ratio $L_{z}/e$, the $Z$ projection of the angular momentum to the eccentricity, as population tracer, which we complement with chemical abundances extracted from the literature and Monte-Carlo simulations. We find that 20 globular clusters belong to the bar/bulge of the Milky Way, 35 exhibit disk properties, and 96 are members of the halo. Moreover, we find that halo globular clusters have close to zero rotational velocity with average value $<Theta>$ =1$pm$ 4 km s$^{-1}$. On the other hand, the sample of clusters that belong to the thick disk possesses a significant rotation with average rotational velocity 179 $pm$ 6 km s$^{-1}$. The twenty globular clusters orbiting within the bar/bulge region of the Milky Way galaxy have average rotational velocity of 49 $pm$ 11 km s$^{-1}$.
We have derived the mean proper motions and space velocities of 154 Galactic globular clusters and the velocity dispersion profiles of 141 globular clusters based on a combination of Gaia DR2 proper motions with ground-based line-of-sight velocities. Combining the velocity dispersion profiles derived here with new measurements of the internal mass functions allows us to model the internal kinematics of 144 clusters, more than 90% of the currently known Galactic globular cluster population. We also derive the initial cluster masses by calculating the cluster orbits backwards in time applying suitable recipes to account for mass loss and dynamical friction. We find a correlation between the stellar mass function of a globular cluster and the amount of mass lost from the cluster, pointing to dynamical evolution as one of the mechanisms shaping the mass function of stars in clusters. The mass functions also show strong evidence that globular clusters started with a bottom-light initial mass function. Our simulations show that the currently surviving globular cluster population has lost about 80% of its mass since the time of formation. If globular clusters started from a log-normal mass function, we estimate that the Milky Way contained about 500 globular clusters initially, with a combined mass of about $2.5 cdot 10^8$ $M_odot$. For a power-law initial mass function, the initial mass in globular clusters could have been a factor of three higher.
Open clusters are key targets for both Galaxy structure and evolution and stellar physics studies. Since textit{Gaia} DR2 publication, the discovery of undetected clusters has proven that our samples were not complete. Our aim is to exploit the Big Data capabilities of machine learning to detect new open clusters in textit{Gaia} DR2, and to complete the open cluster sample to enable further studies on the Galactic disc. We use a machine learning based methodology to systematically search in the Galactic disc, looking for overdensities in the astrometric space and identifying them as open clusters using photometric information. First, we use an unsupervised clustering algorithm, DBSCAN, to blindly search for these overdensities in textit{Gaia} DR2 $(l,b,varpi,mu_{alpha^*},mu_delta)$. After that, we use a deep learning artificial neural network trained on colour-magnitude diagrams to identify isochrone patterns in these overdensities, and to confirm them as open clusters. We find $582$ new open clusters distributed along the Galactic disc, in the region $|b| < 20$. We can detect substructure in complex regions, and identify the tidal tails of a disrupting cluster UBC~$274$ of $sim 3$ Gyr located at $sim 2$ kpc. Adapting the methodology into a Big Data environment allows us to target the search driven by physical properties of the open clusters, instead of being driven by its computational requirements. This blind search for open clusters in the Galactic disc increases in a $45%$ the number of known open clusters.
Line-of-sight kinematic studies indicate that many Galactic globular clusters have a significant degree of internal rotation. However, three-dimensional kinematics from a combination of proper motions and line-of-sight velocities are needed to unveil the role of angular momentum in the formation and evolution of these old stellar systems. Here we present the first quantitative study of internal rotation on the plane-of-the-sky for a large sample of globular clusters using proper motions from Gaia DR2. We detect signatures of rotation in the tangential component of proper motions for 11 out of 51 clusters at a $>$3-sigma confidence level, confirming the detection reported in Gaia collaboration et al. (2018) for 8 clusters, and additionally identify 11 GCs with a 2-sigma rotation detection. For the clusters with a detected global rotation, we construct the two-dimensional rotation maps and proper motion rotation curves, and we assess the relevance of rotation with respect to random motions ($V/sigmasim0.08-0.51$). We find evidence of a correlation between the degree of internal rotation and relaxation time, highlighting the importance of long-term dynamical evolution in shaping the clusters current properties. This is a strong indication that angular momentum must have played a fundamental role in the earliest phases of cluster formation. Finally, exploiting the spatial information of the rotation maps and a comparison with line-of-sight data, we provide an estimate of the inclination of the rotation axis for a subset of 8 clusters. Our work demonstrates the potential of Gaia data for internal kinematic studies of globular clusters and provides the first step to reconstruct their intrinsic three-dimensional structure.
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.
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