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1. Stellar Loci. VII. Photometric Metallicities of 5 Million FGK Stars Based on GALEX GR6+7 AIS and Gaia EDR3

   https://doi.org/10.3847/1538-4365/ad1eea  

   Lu, Xue; Yuan, Haibo; Xu, Shuai; Zhang, Ruoyi; Xiao, Kai; Huang, Yang; Beers, Timothy C; Hong, Jihye (February 2024, The Astrophysical Journal Supplement Series)

   Abstract We combine photometric data from GALEX GR6+7 All-Sky Imaging Survey and Gaia Early Data Release 3 with stellar parameters from the SAGA and PASTEL catalogs to construct high-quality training samples for dwarfs (0.4 < BP − RP < 1.6) and giants (0.6 < BP − RP < 1.6). We apply careful reddening corrections using empirical temperature- and extinction-dependent extinction coefficients. Using the two samples, we establish a relationship between stellar loci (near-ultraviolet (NUV)−BP versus BP − RP colors), metallicity, andM_G. For a given BP − RP color, a 1 dex change in [Fe/H] corresponds to an approximately 1 magnitude change in NUV − BP color for solar-type stars. These relationships are employed to estimate metallicities based on NUV − BP, BP − RP, andM_G. Thanks to the strong metallicity dependence in the GALEX NUV band, our models enable a typical photometric-metallicity precision of approximatelyσ_[Fe/H]= 0.11 dex for dwarfs andσ_[Fe/H]= 0.17 dex for giants, with an effective metallicity range extending down to [Fe/H] = −3.0 for dwarfs and [Fe/H] = −4.0 for giants. We also find that the NUV-band-based photometric-metallicity estimate is not as strongly affected by carbon enhancement as previous photometric techniques. With the GALEX and Gaia data, we have estimated metallicities for about 5 million stars across almost the entire sky, including approximately 4.5 million dwarfs and 0.5 million giants. This work demonstrates the potential of the NUV band for estimating photometric metallicities, and sets the groundwork for utilizing the NUV data from space telescopes such as the upcoming Chinese Space Station Telescope. 

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2. Beyond Spectroscopy. II. Stellar Parameters for over 20 Million Stars in the Northern Sky from SAGES DR1 and Gaia DR3

   https://doi.org/10.3847/1538-4357/ace628  

   Huang, Yang; Beers, Timothy C; Yuan, Haibo; Tan, Ke-Feng; Wang, Wei; Zheng, Jie; Li, Chun; Lee, Young Sun; Li, Hai-Ning; Zhao, Jing-Kun; et al (October 2023, The Astrophysical Journal)

   Abstract We present precise photometric estimates of stellar parameters, including effective temperature, metallicity, luminosity classification, distance, and stellar age, for nearly 26 million stars using the methodology developed in the first paper of this series, based on the stellar colors from the Stellar Abundances and Galactic Evolution Survey (SAGES) Data Release 1 and Gaia Early Data Release 3. The optimal design of stellar-parameter sensitiveuvfilters by SAGES has enabled us to determine photometric-metallicity estimates down to −3.5, similar to our previous results with the SkyMapper Southern Survey (SMSS), yielding a large sample of over five million metal-poor ([Fe/H] ≤ −1.0) stars and nearly one million very metal-poor ([Fe/H] ≤ −2.0) stars. The typical precision is around 0.1 dex for both dwarf and giant stars with [Fe/H] > −1.0, and 0.15–0.25/0.3–0.4 dex for dwarf/giant stars with [Fe/H] < −1.0. Using the precise parallax measurements and stellar colors from Gaia, effective temperature, luminosity classification, distance, and stellar age are further derived for our sample stars. This huge data set in the Northern sky from SAGES, together with similar data in the Southern sky from SMSS, will greatly advance our understanding of the Milky Way, in particular its formation and evolution. 

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3. The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning–based Stellar Parameters for 21 Million Stars from the First Data Release

   https://doi.org/10.3847/1538-4365/adae86  

   Gu, Hongrui; Fan, Zhou; Zhao, Gang; Yang, Huang; Beers, Timothy C; Wang, Wei; Zheng, Jie; Zhao, Jingkun; Li, Chun; Chen, Yuqin; et al (February 2025, The Astrophysical Journal Supplement Series)

   Abstract Stellar parameters for large samples of stars play a crucial role in constraining the nature of stars and stellar populations in the Galaxy. An increasing number of medium-band photometric surveys are presently used in estimating stellar parameters. In this study, we present a machine learning approach to derive estimates of stellar parameters, including [Fe/H], logg, andT_eff, based on a combination of medium-band and broadband photometric observations. Our analysis employs data primarily sourced from the Stellar Abundances and Galactic Evolution Survey (SAGES), which aims to observe much of the Northern Hemisphere. We combine theuv-band data from SAGES DR1 with photometric and astrometric data from Gaia EDR3, and apply the random forest method to estimate stellar parameters for approximately 21 million stars. We are able to obtain precisions of 0.09 dex for [Fe/H], 0.12 dex for logg, and 70 K forT_eff. Furthermore, by incorporating Two Micron All Sky Survey and Wide-field Infrared Survey Explorer infrared photometric and Galaxy Evolution Explorer ultraviolet data, we are able to achieve even higher precision estimates for over 2.2 million stars. These results are applicable to both giant and dwarf stars. Building upon this mapping, we construct a foundational data set for research on metal-poor stars, the structure of the Milky Way, and beyond. With the forthcoming release of additional bands from SAGES such DDO51 and Hα, this versatile machine learning approach is poised to play an important role in upcoming surveys featuring expanded filter sets. 

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4. Candidate Members of the VMP/EMP Disk System of the Galaxy from the SkyMapper and SAGES Surveys

   https://doi.org/10.3847/1538-4365/ad4a6f  

   Hong, Jihye; Beers, Timothy C; Lee, Young Sun; Huang, Yang; Hirai, Yutaka; Cabrera_Garcia, Jonathan; Shank, Derek; Xu, Shuai; Yuan, Haibo; Mardini, Mohammad K; et al (July 2024, The Astrophysical Journal Supplement Series)

   Abstract Photometric stellar surveys now cover a large fraction of the sky, probe to fainter magnitudes than large-scale spectroscopic surveys, and are relatively free from the target selection biases often associated with such studies. Photometric-metallicity estimates that include narrow/medium-band filters can achieve comparable accuracy and precision to existing low-resolution spectroscopic surveys such as Sloan Digital Sky Survey/SEGUE and LAMOST. Here we report on an effort to identify likely members of the Galactic disk system among the very metal-poor (VMP; [Fe/H] ≤ −2) and extremely metal-poor (EMP; [Fe/H] ≤ −3) stars. Our analysis is based on an initial sample of ∼11.5 million stars with full space motions selected from the SkyMapper Southern Survey (SMSS) and Stellar Abundance and Galactic Evolution Survey (SAGES). After applying a number of quality cuts to obtain the best available metallicity and dynamical estimates, we analyze a total of ∼5.86 million stars in the combined SMSS/SAGES sample. We employ two techniques that, depending on the method, identify between 876 and 1476 VMP stars (6.9%−11.7% of all VMP stars) and between 40 and 59 EMP stars (12.4%−18.3% of all EMP stars) that appear to be members of the Galactic disk system on highly prograde orbits (v_ϕ> 150 km s⁻¹). The total number of candidate VMP/EMP disklike stars is 1496, the majority of which have low orbital eccentricities, ecc ≤ 0.4; many have ecc ≤ 0.2. The large fractions of VMP/EMP stars associated with the Milky Way disk system strongly suggest the presence of an early-forming “primordial” disk. 

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5. Additional Evidence for the Existence of a Primordial Disk System

   https://doi.org/10.3847/1538-4357/adf193  

   Xu_徐, Shuai 帅; Yuan_苑, Haibo 海波; Huang_黄, Bowen 博闻; Beers, Timothy C; Huang_黄, Yang 样; Xiang_向, Maosheng 茂盛; Xiao_肖, Kai 凯; Hong, Jihye; Sun_Lee, Young; Yang_杨, Wuming 伍明 (August 2025, The Astrophysical Journal)

   Abstract The origin of very metal-poor (VMP; [Fe/H] ≤ −2.0) stars on planar orbits has been the subject of great attention since their first discovery. However, prior to the release of the Gaia BP/RP (XP) spectra and large photometric samples such as SkyMapper, SAGES, J-PLUS, and S-PLUS, most studies have been limited due to their small sample sizes or strong selection effects. Here, we crossmatch photometric metallicities derived from Gaia XP synthetic photometry and geometric distances from Bailer-Jones et al., and select 12,000 VMP stars (1604 dwarfs and 10,396 giants) with available high-quality astrometry. After calculating dynamical parameter estimates usingAGAMA, we employ the nonnegative matrix factorization technique to thev_ϕdistribution across bins in $Z_{\max }$(the maximum height above or below the Galactic plane during the stellar orbit). We find three primary populations of the selected VMP stars: halo, disk system, and the Gaia Sausage/Enceladus structure. The fraction of disk-like stars decreases with increasing $Z_{\max }$(as expected), although it is still ∼20% for stars with $Z_{\max }$∼ 3 kpc. Similar results emerge from the application of the Hayden criterion, which separates stellar populations on the basis of their orbital inclination angles relative to the Galactic plane. We argue that such high fractions of disk-like stars indicate that they are an independent component, rather than originating solely from Galactic building blocks or heating by minor mergers. We suggest that most of these VMP stars are members of the hypothesized “primordial” disk. 

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