اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدThree new Galactic star clusters discovered in the field of the open cluster NGC 5999 with Gaia DR2
261
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We report the serendipitous discovery of three new open clusters, named UFMG 1, UFMG 2 and UFMG 3 in the field of the intermediate-age cluster NGC 5999, by using Gaia DR2 data. A colour-magnitude filter tailored for a proper selection of main-sequence stars and red clump giants turned evident the presence of NGC 5999 and these three new stellar groups in proper motion space. Their structural parameters were derived from King-profile fittings over their projected stellar distributions and isochrone fits were performed on the clusters cleaned colour-magnitude diagrams built with Gaia bands to derive their astrophysical parameters. The clusters projected sky motion were calculated for each target using our members selection. Distances to the clusters were inferred from stellar parallaxes through a bayesian model, showing that they are marginally consistent with their isochronal distances, considering the random and systematic uncertainties involved. The new clusters are located in the nearby Sagittarius arm (d ~ 1.5 kpc) with NGC 5999 at the background (d ~ 1.8 kpc). They contain at least a few hundred stars of nearly solar metallicity and have ages between 100 and 1400 Myr.
قيم البحث
اقرأ أيضاً
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 D
ata 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.
Open clusters (OCs) are popular tracers of the structure and evolutionary history of the Galactic disk. The OC population is often considered to be complete within 1.8 kpc of the Sun. The recent Gaia Data Release 2 (DR2) allows the latter claim to be
challenged. We perform a systematic search for new OCs in the direction of Perseus using precise and accurate astrometry from Gaia DR2. We implement a coarse-to-fine search method. First, we exploit spatial proximity using a fast density-aware partitioning of the sky via a k-d tree in the spatial domain of Galactic coordinates, (l, b). Secondly, we employ a Gaussian mixture model in the proper motion space to quickly tag fields around OC candidates. Thirdly, we apply an unsupervised membership assignment method, UPMASK, to scrutinise the candidates. We visually inspect colour-magnitude diagrams to validate the detected objects. Finally, we perform a diagnostic to quantify the significance of each identified overdensity in proper motion and in parallax space We report the discovery of 41 new stellar clusters. This represents an increment of at least 20% of the previously known OC population in this volume of the Milky Way. We also report on the clear identification of NGC 886, an object previously considered an asterism. This letter challenges the previous claim of a near-complete sample of open clusters up to 1.8 kpc. Our results reveal that this claim requires revision, and a complete census of nearby open clusters is yet to be found.
VISTA Variables in the V{i}a Lactea (VVV) is one of the six ESO Public Surveys operating on the new 4-meter Visible and Infrared Survey Telescope for Astronomy (VISTA). VVV is scanning the Milky Way bulge and an adjacent section of the disk, where st
ar formation activity is high. One of the principal goals of the VVV Survey is to find new star clusters of different ages. In order to trace the early epochs of star cluster formation we concentrated our search in the directions to those of known star formation regions, masers, radio, and infrared sources. The disk area covered by VVV was visually inspected using the pipeline processed and calibrated $K_{rm S}$-band tile images for stellar overdensities. Subsequently, we examined the composite $JHK_{rm S}$ and $ZJK_{rm S}$ color images of each candidate. PSF photometry of $15times15$ arcmin fields centered on the candidates was then performed on the Cambridge Astronomy Survey Unit reduced images. After statistical field-star decontamination, color-magnitude and color-color diagrams were constructed and analyzed. We report the discovery of 96 new infrared open clusters and stellar groups. Most of the new cluster candidates are faint and compact (with small angular sizes), highly reddened, and younger than 5,Myr. For relatively well populated cluster candidates we derived their fundamental parameters such as reddening, distance, and age by fitting the solar-metallicity Padova isochrones to the color-magnitude diagrams.
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 ne
w 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. Open clusters are very good tracers of the evolution of the Galactic disc. Thanks to Gaia, their kinematics can be investigated with an unprecedented precision and accuracy. Aims. The distribution of open clusters in the 6D phase space is re
visited with Gaia DR2. Methods. The weighted mean radial velocity of open clusters was determined, using the most probable members available from a previous astrometric investigation that also provided mean parallaxes and proper motions. Those parameters, all derived from Gaia DR2 only, were combined to provide the 6D phase space information of 861 clusters. The velocity distribution of nearby clusters was investigated, as well as the spatial and velocity distributions of the whole sample as a function of age. A high quality subsample was used to investigate some possible pairs and groups of clusters sharing the same Galactic position and velocity. Results. For the high quality sample that has 406 clusters, the median uncertainty of the weighted mean radial velocity is 0.5 km/s. The accuracy, assessed by comparison to ground-based high resolution spectroscopy, is better than 1 km/s. Open clusters nicely follow the velocity distribution of field stars in the close Solar neighbourhood previously revealed by Gaia DR2. As expected, the vertical distribution of young clusters is very flat but the novelty is the high precision to which this can be seen. The dispersion of vertical velocities of young clusters is at the level of 5 km/s. Clusters older than 1 Gyr span distances to the Galactic plane up to 1 kpc with a vertical velocity dispersion of 14 km/s, typical of the thin disc. Five pairs of clusters and one group with five members are possibly physically related. Other binary candidates previously identified turn out to be chance alignment.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
