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Abstract The stellar atmospheric parameters and physical properties of stars in the Kepler Input Catalog (KIC) are of great significance for the study of exoplanets, stellar activity, and asteroseismology. However, despite extensive effort over the past decades, accurate spectroscopic estimates of these parameters are available for only about half of the stars in the full KIC. In our work, by training relationships between photometric colors and spectroscopic stellar parameters from Gaia DR3, the Kepler-INT Survey, Large Sky Area Multi-Object Fiber Spectroscopic Telescope DR10, and Galactic Evolution Experiment at Apache Point Observatory DR17, we have obtained atmospheric parameter estimates for over 195,000 stars, accounting for 97% of the total sample of KIC stars. We obtain 1σuncertainties of 0.1 dex on metallicity [Fe/H], 100 K on effective temperatureT_eff, and 0.2 dex on surface gravity logg. In addition, based on these atmospheric parameters, we estimated the ages, masses, radii, and surface gravities of these stars using the commonly adopted isochrone-fitting approach. External comparisons indicate that the resulting precision for turnoff stars is 20% in age; for dwarf stars, it is 0.07M_⊙in mass, 0.05R_⊙in radius, and 0.12 dex in surface gravity; and for giant stars, it is 0.14M_⊙in mass, 0.73R_⊙in radius, and 0.11 dex in surface gravity. 

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 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 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.