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Abstract We present maps of the mean metallicity distributions on the GalactocentricR–Zplane at different azimuthal angles using red clump stars selected from the LAMOST and APOGEE surveys. In the inner disk (R < 11 kpc), the metallicity distribution is symmetric between the upper and lower disk. However, we find a north–south metallicity asymmetry in the outer disk (R > 11 kpc), especially toward the anti-Galactic center (−5^∘ < Φ < 15°) direction. By further dissecting the map in age space, we detect this asymmetry across all mono-age stellar populations. However, the asymmetry is less pronounced in older populations (τ > 8 Gyr) compared to younger ones (τ < 6 Gyr). This reduced significance likely stems from three factors: larger age uncertainties, fewer stars in the outer disk, and the kinematically hotter nature of older populations. The observed metallicity asymmetry may be the consequence of the perturbation of the recent pericentric passage through the Galactic disk and tidal force of the well-known Sagittarius dwarf galaxy. 

Abstract We present a pioneering achievement in the high-precision photometric calibration of CMOS-based photometry, by application of the Gaia Blue Photometer or Red Photometer (XP) spectra–based synthetic photometry method to the mini-SiTian array (MST) photometry. Through 79 repeated observations of thef02field on the night, we find good internal consistency in the calibrated MSTG_MST-band magnitudes for relatively bright stars, with a precision of about 4 mmag forG_MST ∼ 13. Results from more than 30 different nights (over 3100 observations) further confirm this internal consistency, indicating that the 4 mmag precision is stable and achievable over timescales of months. An independent external validation using spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope DR10 and high-precision photometric data using CCDs from Gaia DR3 reveals a zero-point consistency better than 1 mmag. Our results clearly demonstrate that CMOS photometry is on par with CCD photometry for high-precision results, highlighting the significant capabilities of CMOS cameras in astronomical observations, especially for large-scale telescope survey arrays. 

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. 

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. 

Abstract We present an independent validation and comprehensive recalibration of S-PLUS Ultra-short Survey (USS) DR1 12-band photometry using about 30,000–70,000 standard stars from the Best Star (BEST) database. We identify the spatial variation of zero-point offsets, up to 30–40 mmag for blue filters (u,J0378, andJ0395) and 10 mmag for others, predominantly due to the higher uncertainties of the technique employed in the original USS calibration. Moreover, we detect large- and medium-scale CCD position-dependent systematic errors, up to 50 mmag, primarily caused by different aperture and flat-field corrections. We then recalibrate the USS DR1 photometry by correcting the systematic shifts for each tile using second-order two-dimensional polynomial fitting combined with a numerical stellar flat-field correction method. The recalibrated results from the XP spectrum based synthetic photometry and the stellar color regression standards are consistent within 6 mmag in the USS zero-points, demonstrating both the typical precision of the recalibrated USS photometry and a sixfold improvement in USS zero-point precision. Further validation using the Sloan Digital Sky Survey and Pan-STARRS1, as well as LAMOST DR10 and Gaia photometry, also confirms this precision for the recalibrated USS photometry. Our results clearly demonstrate the capability and efficiency of the BEST database in improving calibration precision to the millimagnitude level for wide-field photometric surveys. The recalibrated USS DR1 photometry is publicly available on ChinaVO at doi:10.12149/101503. 

Abstract We search for an optimal filter design for the estimation of stellar metallicity, based on synthetic photometry from Gaia XP spectra convolved with a series of filter-transmission curves defined by different central wavelengths and bandwidths. Unlike previous designs based solely on maximizing metallicity sensitivity, we find that the optimal solution provides a balance between the sensitivity and uncertainty of the spectra. With this optimal filter design, the best precision of metallicity estimates for relatively bright (G∼ 11.5) stars is excellent,σ_[Fe/H]= 0.034 dex for FGK dwarf stars, superior to that obtained utilizing custom sensitivity-optimized filters (e.g., SkyMapperv). By selecting hundreds of high-probability member stars of the open cluster M67, our analysis reveals that the intrinsic photometric-metallicity scatter of these cluster members is only 0.036 dex, consistent with this level of precision. Our results clearly demonstrate that the internal precision of photometric-metallicity estimates can be extremely high, even providing the opportunity to perform chemical tagging for very large numbers of field stars in the Milky Way. This experiment shows that it is crucial to take into account uncertainty alongside the sensitivity when designing filters for measuring the stellar metallicity and other parameters. 

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. 

Abstract We present a comprehensive recalibration of narrowband/medium-band and broadband photometry from the Southern Photometric Local Universe Survey (S-PLUS) by leveraging two approaches: an improved Gaia XP synthetic photometry (XPSP) method with corrected Gaia XP spectra, and the stellar color regression (SCR) method with corrected Gaia Early Data Release 3 photometric data and spectroscopic data from LAMOST Data Release 7. Through the use of millions of stars as standards per band, we demonstrate the existence of position-dependent systematic errors, up to 23 mmag for the main survey region, in the S-PLUS iDR4 photometric data. A comparison between the XPSP and SCR methods reveals minor differences in zero-point offsets, typically within the range of 1–6 mmag, indicating the accuracy of the recalibration, and a twofold to threefold improvement in the zero-point precision. During this process, we also verify and correct for systematic errors related to CCD position. The corrected S-PLUS iDR4 photometric data will provide a solid data foundation for conducting scientific research that relies on high-precision calibration. Our results underscore the power of the XPSP method in combination with the SCR method, showcasing their effectiveness in enhancing calibration precision for wide-field surveys when combined with Gaia photometry and XP spectra, to be applied for other S-PLUS subsurveys. 

Abstract We employ the corrected Gaia Early Data Release 3 photometric data and spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR7 to assemble a sample of approximately 0.25 million FGK dwarf photometric standard stars for the 12 J-PLUS filters using the stellar color regression (SCR) method. We then independently validate the J-PLUS DR3 photometry and uncover significant systematic errors: up to 15 mmag in the results from the stellar locus method and up to 10 mmag primarily caused by magnitude-, color-, and extinction-dependent errors of the Gaia XP spectra as revealed by the Gaia BP/RP (XP) synthetic photometry (XPSP) method. We have also further developed the XPSP method using the corrected Gaia XP spectra by B. Huang et al. and applied it to the J-PLUS DR3 photometry. This resulted in an agreement of 1–5 mmag with the SCR method and a twofold improvement in the J-PLUS zero-point precision. Finally, the zero-point calibration for around 91% of the tiles within the LAMOST observation footprint is determined through the SCR method, with the remaining approximately 9% of the tiles outside this footprint relying on the improved XPSP method. The recalibrated J-PLUS DR3 photometric data establish a solid data foundation for conducting research that depends on high-precision photometric calibration.