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We derive distances and masses of stars from the Sloan Digital Sky Survey (SDSS) Apache Point Observatory Galactic Evolution Experiment Data Release 17 using simple neural networks. Training data for distances comes from Gaia EDR3, supplemented by literature distances for star clusters. For masses, the network is trained using asteroseismic masses for evolved stars and isochrone masses for main-sequence stars. The models are trained on effective temperature, surface gravity, metallicity, and carbon and nitrogen abundances. We found that our distance predictions have median fractional errors that range from ≈20% at low loggand ≈10% at higher loggwith a standard deviation of ≈11%. The mass predictions have a standard deviation of ±12%. Using the masses, we derive ages for evolved stars based on the correspondence between mass and age for giant stars given by isochrones. The results are compiled into a Value Added Catalog called DistMass that contains distances and masses for 733,901 independent spectra, plus ages for 396,548 evolved stars.

 

Accurate stellar ages are essential for our understanding of the star formation history of the Milky Way and Galactic chemical evolution, as well as to constrain exoplanet formation models. Gyrochronology, a relationship between stellar rotation and age, appears to offer a reliable age indicator for main-sequence (MS) stars over the mass range of approximately 0.6–1.3M_⊙. Those stars lose their angular momentum due to magnetic braking and as a result their rotation speeds decrease with age. Although current gyrochronology relations have been fairly well tested for young MS stars with masses greater than 1M_⊙, primarily in young open clusters, insufficient tests exist for older and lower mass MS stars. Binary stars offer the potential to expand and fill in the range of ages and metallicity over which gyrochronology can be empirically tested. In this paper, we demonstrate a Monte Carlo approach to evaluate gyrochronology models using binary stars. As examples, we used five previously published wide binary pairs. We also demonstrate a Monte Carlo approach to assess the precision and accuracy of ages derived from each gyrochronology model. For the traditional Skumanich models, the age uncertainties areσ_age/age = 15%–20% for stars withB−V= 0.65 andσ_age/age = 5%–10% for stars withB−V= 1.5 and rotation periodP≤ 20 days.

 

We present new maps of the Milky Way disk showing the distribution of metallicity ([Fe/H]),α-element abundances ([Mg/Fe]), and stellar age, using a sample of 66,496 red giant stars from the final data release (DR17) of the Apache Point Observatory Galactic Evolution Experiment survey. We measure radial and vertical gradients, quantify the distribution functions for age and metallicity, and explore chemical clock relations across the Milky Way for the low-αdisk, high-αdisk, and total population independently. The low-αdisk exhibits a negative radial metallicity gradient of −0.06 ± 0.001 dex kpc⁻¹, which flattens with distance from the midplane. The high-αdisk shows a flat radial gradient in metallicity and age across nearly all locations of the disk. The age and metallicity distribution functions shift from negatively skewed in the inner Galaxy to positively skewed at large radius. Significant bimodality in the [Mg/Fe]–[Fe/H] plane and in the [Mg/Fe]–age relation persist across the entire disk. The age estimates have typical uncertainties of ∼0.15 in log(age) and may be subject to additional systematic errors, which impose limitations on conclusions drawn from this sample. Nevertheless, these results act as critical constraints on galactic evolution models, constraining which physical processes played a dominant role in the formation of the Milky Way disk. We discuss how radial migration predicts many of the observed trends near the solar neighborhood and in the outer disk, but an additional more dramatic evolution history, such as the multi-infall model or a merger event, is needed to explain the chemical and age bimodality elsewhere in the Galaxy.

 

Abstract This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.