Gaia keeps on delivering: expanding the open cluster population with EDR3

Stars and planetary system

Gaia keeps on delivering: expanding the open cluster population with EDR3

Stars and planetary system

Hunting for open clusters in \textit{Gaia} DR2: the Galactic anticentre

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 search for unknown stellar structures. Particularly, supervised and unsupervised learning methods combined together significantly improves the detection rate of open clusters. We systematically scan Gaia DR2 in a region covering the Galactic anticentre and the Perseus arm $(120 \leq l \leq 205$ and $-10 \leq b \leq 10)$, with the goal of finding any open clusters that may exist in this region, and fine tuning a previously proposed methodology successfully applied to TGAS data, adapting it to different density regions. Our methodology uses an unsupervised, density-based, clustering algorithm, DBSCAN, that identifies overdensities in the five-dimensional astrometric parameter space $(l,b,\varpi,\mu_{\alpha^*},\mu_{\delta})$ that may correspond to physical clusters. The overdensities are separated into physical clusters (open clusters) or random statistical clusters using an artificial neural network to recognise the isochrone pattern that open clusters show in a colour magnitude diagram. The method is able to recover more than 75% of the open clusters confirmed in the search area. Moreover, we detected 53 open clusters unknown previous to Gaia DR2, which represents an increase of more than 22% with respect to the already catalogued clusters in this region. We find that the census of nearby open clusters is not complete. Different machine learning methodologies for a blind search of open clusters are complementary to each other; no single method is able to detect 100% of the existing groups. Our methodology has shown to be a reliable tool for the automatic detection of open clusters, designed to be applied to the full Gaia DR2 catalogue.Comment: 8 pages, accepted by Astronomy and Astrophysics (A&A) the 14th May, 2019. Tables 1 and 2 available at the CD

Gaia kinematics reveal a complex lopsided and twisted Galactic disc warp

There are few warp kinematic models of the Galaxy able to characterise structure and kinematics. These models are necessary to study the lopsidedness of the warp and the twisting of the line-of-nodes of the stellar warp, already seen in gas and dust. We use the \Gaia~Data Release 2 astrometric data up to $G=20$mag to characterise the structure of the Galactic warp, the vertical motions and the dependency on the age. We use two populations up to galactocentric distances of $16$kpc, a young (OB-type) and an old (Red Giant Branch, RGB). We use the nGC3 PCM and LonKin methods based on the Gaia observables, together with 2D projections of the positions and proper motions in the Galactic plane. We confirm the age dependency of the Galactic warp, both in positions and kinematics, being the height of the Galactic warp of about $0.2$kpc for the OB sample and of $1.$kpc for the RGB at a galactocentric distance of $14$kpc. Both methods find that the onset radius is $12\sim 13$kpc for the OB sample and $10\sim 11$kpc for the RGB. From the RGB sample, we find from galactocentric distances larger than $10$kpc the line-of-nodes twists away from the Sun-anticentre line towards galactic azimuths $\sim 180-200^{\circ}$ increasing with radius, though possibly influenced by extinction. The RGB sample reveals a slightly lopsided stellar warp with $\sim 250$pc between the up and down sides. The line of maximum of proper motions in latitude is systematically offset from the line-of-nodes estimated from the spatial data, which our models predict as a kinematic signature of lopsidedness. We also show a prominent wave-like pattern of a bending mode different in the OB and RGB, and substructures that might not be related to the Galactic warp nor to a bending mode. GDR2 triggers the need for complex kinematic models, flexible enough to combine both wave-like patterns and an S-shaped lopsided warp.[abridged]Comment: 14 pages (+7 pages of appendix), matches the accepted version in A&A after referee comments (June 5th 2019

A machine learning-based tool for open cluster membership determination in Gaia DR3

Membership studies characterising open clusters with Gaia data, most using DR2, are so far limited at magnitude G = 18 due to astrometric uncertainties at the faint end. Our goal is to extend current open cluster membership lists with faint members and to characterise the low-mass end, which members are important for many applications, in particular for ground-based spectroscopic surveys. We use a deep neural network architecture to learn the distribution of highly reliable open cluster member stars around known clusters. After that, we use the trained network to estimate new open cluster members based on their similarities in a high-dimensional space, five-dimensional astrometry plus the three photometric bands. Due to the improved astrometric precisions of Gaia DR3 with respect to DR2, we are able to homogeneously detect new faint member stars (G > 18) for the known open cluster population. Our methodology can provide extended membership lists for open clusters down to the limiting magnitude of Gaia, which will enable further studies to characterise the open cluster population, e.g. estimation of their masses, or their dynamics. These extended membership lists are also ideal target lists for forthcoming ground-based spectroscopic surveys.Comment: 10 pages, 6 figures. Submitted to Astronomy & Astrophysic

The (im)possibility of strong chemical tagging

Interstellar matter and star formatio

NGC 1605 is not a binary cluster

Stars and planetary system

The Sagittarius stream with Gaia data

The in-fall of the Sagittarius Dwarf Spheroidal (Sgr) has possibly been responsible of important perturbations on the Milky Way (MW) disk. Yet, with only some thousand of line-of-sight velocities and very few astrometric measurements, there are still many open questions regarding its orbit and stellar content, which hinders our ability to constrain its effects on the MW. We present the largest sample of Sagittarius dwarf and stream stars available to date, obtained entirely by searching in the Gaia DR2 proper motions. Thanks to a smart use of the Gaia Archive combined with the Wavelet Transform to detect substructure, we have unveiled the stream and its proper motion in an almost 360° of its path on the sky, being the more extended and continuous proper motion sequence ever measured for a stream. We have also obtained a sample of RR Lyrae in the stream for which we gain access to the distances and, therefore, to the tangential velocities for the first time. We show the main kinematic and population characteristics of the stream derived in our study. A first comparison with one of the most successful models of the stream shows significant kinematical differences with the data. Our data will allow us to study the detailed the populations of Sgr, obtain the best possible fit to the MW potential from its orbit and, in turn, constrain its impact on our Galaxy

The Halo-Disc dynamical coupling:Gaia blind detection of the Monoceros and ACS structures

The astrometric sample provided by Gaia allows us to study the disc far from the Sun, in the halo and at their interface. It is at the very edge of the disc where the effects of external perturbations is most noticeable, but also where there could be the remnants of accreted satellites. Our goal is to characterise the kinematic substructure present at the edge of the Milky Way (MW) disc to provide observational constrains that can help us identify their origin. We present the most precise characterisation of Monoceros and the Anticentre stream (ACS), detected for the first time exclusively in phase-space, without limiting ourselves to a particular stellar type. Our results allow future works to model their orbital parameters, chemistry and star formation history, to establish their origin and, ultimately, understand the most influential processes that shaped the MW over its history