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Free, publicly-accessible full text available July 1, 2026
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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 temperatureTeff, 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.more » « lessFree, publicly-accessible full text available February 17, 2026
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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 MSTGMST-band magnitudes for relatively bright stars, with a precision of about 4 mmag forGMST ∼ 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.more » « lessFree, publicly-accessible full text available March 19, 2026
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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.more » « less
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