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1. The Hubble Space Telescope UV Legacy Survey of Galactic Globular Clusters. XXIII. Proper-motion Catalogs and Internal Kinematics

   https://doi.org/10.3847/1538-4357/ac7727  

   Libralato, Mattia; Bellini, Andrea; Vesperini, Enrico; Piotto, Giampaolo; Milone, Antonino P.; van der Marel, Roeland P.; Anderson, Jay; Aparicio, Antonio; Barbuy, Beatriz; Bedin, Luigi R.; et al (August 2022, The Astrophysical Journal)

   Abstract A number of studies based on the data collected by the Hubble Space Telescope (HST) GO-13297 program “HST Legacy Survey of Galactic Globular Clusters: Shedding UV Light on Their Populations and Formation” have investigated the photometric properties of a large sample of Galactic globular clusters and revolutionized our understanding of their stellar populations. In this paper, we expand upon previous studies by focusing our attention on the stellar clusters’ internal kinematics. We computed proper motions for stars in 56 globular clusters and one open cluster by combining the GO-13297 images with archival HST data. The astrophotometric catalogs released with this paper represent the most complete and homogeneous collection of proper motions of stars in the cores of stellar clusters to date, and expand the information provided by the current (and future) Gaia data releases to much fainter stars and into the crowded central regions. We also census the general kinematic properties of stellar clusters by computing the velocity dispersion and anisotropy radial profiles of their bright members. We study the dependence on concentration and relaxation time, and derive dynamical distances. Finally, we present an in-depth kinematic analysis of the globular cluster NGC 5904. 

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2. Dynamical masses and mass-to-light ratios of resolved massive star clusters – I. NGC 419 and NGC 1846

   https://doi.org/10.1093/mnras/stz2502  

   Song, Ying-Yi; Mateo, Mario; Mackey, A D; Olszewski, Edward W; Roederer, Ian U; Walker, Matthew G; Bailey, John I (November 2019, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT As an introduction of a kinematic survey of Magellanic Cloud (MC) star clusters, we report on the dynamical masses and mass-to-light ratios (M/L) of NGC 419 (Small Magellanic Cloud) and NGC 1846 (Large Magellanic Cloud). We have obtained more than one hundred high-resolution stellar spectra in and around each cluster using the multi-object spectrograph M2FS on the Magellan/Clay Telescope. Line-of-sight velocities and positions of the stars observed in each cluster were used as input to an expectation-maximization algorithm used to estimate cluster membership probabilities, resulting in samples of 46 and 52 likely members (PM ≥ 50 per cent) in NGC 419 and NGC 1846, respectively. This process employed single-mass King models constrained by the structural parameters of the clusters and provided self-consistent dynamical mass estimates for both clusters. Our best-fitting results show that NGC 419 has a projected central velocity dispersion of $$2.44^{+0.37}_{-0.21}$$ km s−1, corresponding to a total mass of $$7.6^{+2.5}_{-1.3}\times 10^4\ {\rm M}_{\odot }$$ and V-band M/L ratio of $$0.22^{+0.08}_{-0.05}$$ in solar units. For NGC 1846, the corresponding results are $$2.04^{+0.28}_{-0.24}$$ km s−1, $$5.4^{+1.5}_{-1.4}\times 10^4\ {\rm M}_{\odot }$$, and $$0.32^{+0.11}_{-0.11}$$. The mean metallicities of NGC 419 and NGC 1846 are found to be $$\rm [Fe/H]=-0.84\pm 0.19$$ and −0.70 ± 0.08, respectively, based on the spectra of likely cluster members. We find marginal statistical evidence of rotation in both clusters, though in neither cluster does rotation alter our mass estimates significantly. We critically compare our findings with those of previous kinematic studies of these two clusters in order to evaluate the consistency of our observational results and analytic tools. 

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3. Possibilities and Limitations of Kinematically Identifying Stars from Accreted Ultra-faint Dwarf Galaxies

   https://doi.org/10.3847/1538-4357/ac85b9  

   Brauer, Kaley; Andales, Hillary Diane; Ji, Alexander P.; Frebel, Anna; Mardini, Mohammad K.; Gómez, Facundo A.; O’Shea, Brian W. (September 2022, The Astrophysical Journal)

   Abstract The Milky Way has accreted many ultra-faint dwarf galaxies (UFDs), and stars from these galaxies can be found throughout our Galaxy today. Studying these stars provides insight into galaxy formation and early chemical enrichment, but identifying them is difficult. Clustering stellar dynamics in 4D phase space ( E , L z , J r , J z ) is one method of identifying accreted structure that is currently being utilized in the search for accreted UFDs. We produce 32 simulated stellar halos using particle tagging with the Caterpillar simulation suite and thoroughly test the abilities of different clustering algorithms to recover tidally disrupted UFD remnants. We perform over 10,000 clustering runs, testing seven clustering algorithms, roughly twenty hyperparameter choices per algorithm, and six different types of data sets each with up to 32 simulated samples. Of the seven algorithms, HDBSCAN most consistently balances UFD recovery rates and cluster realness rates. We find that, even in highly idealized cases, the vast majority of clusters found by clustering algorithms do not correspond to real accreted UFD remnants and we can generally only recover 6% of UFDs remnants at best. These results focus exclusively on groups of stars from UFDs, which have weak dynamic signatures compared to the background of other stars. The recoverable UFD remnants are those that accreted recently, z accretion ≲ 0.5. Based on these results, we make recommendations to help guide the search for dynamically linked clusters of UFD stars in observational data. We find that real clusters generally have higher median energy and J r , providing a way to help identify real versus fake clusters. We also recommend incorporating chemical tagging as a way to improve clustering results. 

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4. Revealing the Milky Way’s most recent major merger with a Gaia EDR3 catalogue of machine-learned line-of-sight velocities

   https://doi.org/10.1093/mnras/stad209  

   Dropulic, Adriana; Liu, Hongwan; Ostdiek, Bryan; Lisanti, Mariangela (March 2023, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT Machine learning can play a powerful role in inferring missing line-of-sight velocities from astrometry in surveys such as Gaia. In this paper, we apply a neural network to Gaia Early Data Release 3 (EDR3) and obtain line-of-sight velocities and associated uncertainties for ∼92 million stars. The network, which takes as input a star’s parallax, angular coordinates, and proper motions, is trained and validated on ∼6.4 million stars in Gaia with complete phase-space information. The network’s uncertainty on its velocity prediction is a key aspect of its design; by properly convolving these uncertainties with the inferred velocities, we obtain accurate stellar kinematic distributions. As a first science application, we use the new network-completed catalogue to identify candidate stars that belong to the Milky Way’s most recent major merger, Gaia-Sausage-Enceladus (GSE). We present the kinematic, energy, angular momentum, and spatial distributions of the ∼450 000 GSE candidates in this sample, and also study the chemical abundances of those with cross matches to GALAH and APOGEE. The network’s predictive power will only continue to improve with future Gaia data releases as the training set of stars with complete phase-space information grows. This work provides a first demonstration of how to use machine learning to exploit high-dimensional correlations on data to infer line-of-sight velocities, and offers a template for how to train, validate, and apply such a neural network when complete observational data is not available. 

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5. Blanco DECam Bulge Survey (BDBS). VII. Multiple Populations in Globular Clusters of the Galactic Bulge

   https://doi.org/10.3847/1538-4357/ac94c5  

   Kader, Justin A.; Pilachowski, Catherine A.; Johnson, Christian I.; Rich, R. Michael; Young, Michael D.; Simion, Iulia T.; Clarkson, William I.; Michael, Scott; Kunder, Andrea; Vivas, Anna Katherina; et al (November 2022, The Astrophysical Journal)

   Abstract We present photometric evidence for multiple stellar populations (MPs) in 14 globular clusters (GCs) toward the southern Galactic bulge. The photometric data come as part of the Blanco DECam Bulge Survey, which is a deep, wide-field near-UV-near-IR ( ugriz Y) survey of the southern Galactic bulge. Here, we present the first systematic study of bulge GC multiple populations with deep photometry including the u band, which is a crucial indicator of the abundance of CNO-bearing molecules in stellar atmospheres. We identify cluster members using Gaia EDR3 proper motion measurements, and then isolate red giant branch stars using r versus u − r color–magnitude diagrams. We find evidence suggesting all 14 clusters host at least two populations, and NGC 6441, NGC 6626, and NGC 6656 appear to have at least three populations. Many of these clusters are not part of the Hubble Space Telescope (HST) surveys nor do they have comprehensive spectroscopic analyses so we are presenting the first evidence of MPs in several clusters. Not only do we find a strong anticorrelation between the fraction of first-generation stars and cluster absolute V magnitude, but the correlation coefficient and cluster-to-cluster scatter are similar to the results obtained from HST. Our ground-based data extend to much larger radial distances than similar HST observations, enabling a reliable estimate of the global fraction of first-generation stars in each cluster. This study demonstrates that ground-based u -band photometry as provided by DECam will prove powerful in the study of multiple populations in resolved GCs. 

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