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Gaia DR3 photometry and BP/RP spectra have been widely used as reference in photometric calibrations. In this work, we check the spatial uniformity of Gaia DR3 photometry and BP/RP spectra by comparing the BP, RP and G bands photometry with the synthetic ones from the BP/RP spectra. The discrepancies have a small dispersion of 1.07, 0.55 and 1.02 mmag for the BP, RP, and G bands, respectively. However, the discrepancies exhibit obvious spatial patterns, which are clearly associated with the Gaia's scanning law. The patterns observed in the BP and G bands are similar, with discrepancies between photometry and spectra being more pronounced in these bands compared to the RP band. A further independent test with the Dark Energy Survey DR2 photometry reveals that the spatial patterns are more likely attributed to the Gaia DR3 BP/RP spectra, particularly in the BP band. On one hand, our results confirm the high spatial uniformity of Gaia data at the mmag level. On the other hand, our results suggest that the spatial uniformity of Gaia DR3 BP/RP spectra is not as good as that of Gaia DR3 photometry, and could be further improved in the future., Comment: 7pages, 2 figures, ApJ accepted

We present a catalog of stellar parameters (effective temperature $T_{\rm eff}$, surface gravity $\log g$, age, and metallicity [Fe/H]) and elemental-abundance ratios ([C/Fe], [Mg/Fe], and [$\alpha$/Fe]) for some five million stars (4.5 million dwarfs and 0.5 million giants stars) in the Milky Way, based on stellar colors from the Javalambre Photometric Local Universe Survey (J-PLUS) DR3 and \textit{Gaia} EDR3. These estimates are obtained through the construction of a large spectroscopic training set with parameters and abundances adjusted to uniform scales, and trained with a Kernel Principal Component Analysis. Owing to the seven narrow/medium-band filters employed by J-PLUS, we obtain precisions in the abundance estimates that are as good or better than derived from medium-resolution spectroscopy for stars covering a wide range of the parameter space: 0.10-0.20 dex for [Fe/H] and [C/Fe], and 0.05 dex for [Mg/Fe] and [$\alpha$/Fe]. Moreover, systematic errors due to the influence of molecular carbon bands on previous photometric-metallicity estimates (which only included two narrow/medium-band blue filters) have now been removed, resulting in photometric-metallicity estimates down to [Fe/H] $\sim -4.0$, with typical uncertainties of 0.25 dex and 0.40 dex for dwarfs and giants, respectively. This large photometric sample should prove useful for the exploration of the assembly and chemical-evolution history of our Galaxy., Comment: 31 pages, 20 figures, 3 tables, accepeted by ApJ

We present a direct measurement of extinction curves using corrected $Gaia$ XP spectra of the common sources in $Gaia$ DR3 and LAMOST DR7. Our analysis of approximately 370 thousand high-quality samples yielded a high-precision average extinction curve for the Milky Way. After incorporating infrared photometric data from 2MASS and WISE, the extinction curve spans wavelengths from 0.336 to 4.6 $\mu$m. We determine an average $R_{55}$ of $2.730 \pm 0.007$, corresponding to $R_V= 3.073 \pm 0.009$, and a near-infrared power-law index $\alpha$ of $1.935 \pm 0.037$. Our study confirmed some intermediate-scale structures within the optical range. Two new features were identified at 540 and 769 nm, and their intensities exhibited a correlation with extinction and $R_V$. This extinction curve can be used to investigate the characteristics of dust and enhance the extinction correction of Milky Way stars. A Python package for this extinction curve is available., Comment: 11 pages, 5 figures, accepted for publication in ApJ

The shape of the dark matter (DM) halo is key to understanding the hierarchical formation of the Galaxy. Despite extensive efforts in recent decades, however, its shape remains a matter of debate, with suggestions ranging from strongly oblate to prolate. Here, we present a new constraint on its present shape by directly measuring the evolution of the Galactic disk warp with time, as traced by accurate distance estimates and precise age determinations for about 2,600 classical Cepheids. We show that the Galactic warp is mildly precessing in a retrograde direction at a rate of $\omega = -2.1 \pm 0.5 ({\rm statistical}) \pm 0.6 ({\rm systematic})$ km s$^{-1}$ kpc$^{-1}$ for the outer disk over the Galactocentric radius [$7.5, 25$] kpc, decreasing with radius. This constrains the shape of the DM halo to be slightly oblate with a flattening (minor axis to major axis ratio) in the range $0.84 \le q_{\Phi} \le 0.96$. Given the young nature of the disk warp traced by Cepheids (less than 200 Myr), our approach directly measures the shape of the present-day DM halo. This measurement, combined with other measurements from older tracers, could provide vital constraints on the evolution of the DM halo and the assembly history of the Galaxy., Comment: Published in Nature Astronomy on June 27th, 2024. Final published version here: https://www.nature.com/articles/s41550-024-02309-5

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 ($G \sim 11.5$) stars is excellent, $\sigma_{\rm [Fe/H]} = 0.034$\,dex for FGK dwarf stars, superior to that obtained utilizing custom sensitivity-optimized filters (e.g., SkyMapper\,$v$). By selecting hundreds of high-probabability 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., Comment: 9 pages, 5 figures; ApJL accepted, see main result in Figures 5

During the early merger of the Milky Way, intermediate-mass black holes in merged dwarf galaxies may have been ejected from the center of their host galaxies due to gravitational waves, carrying some central stars along. This process can lead to the formation of hyper-compact star clusters, potentially hosting black holes in the mass range of $10^4$ to $10^5$ solar masses. These clusters are crucial targets for identifying and investigating intermediate-mass black holes. However, no hyper-compact star clusters in the Milky Way have been identified so far. In this paper, taking advantage of the high spatial resolution power of Gaia, we used data from Gaia EDR3 and LAMOST DR7, along with additional data from Pan-STARRS and SDSS, to conduct an initial screening of 6,138,049 sources using various parameters of Gaia EDR3. A total of 4,786 sources were selected for in-depth analysis. Each of these sources was meticulously scrutinized by examining their images, spectra, and nearby celestial objects to exclude various false positives, such as contaminations, galaxies, wide binaries, or wrong matches. We finally identified one likely hyper-compact star cluster candidate in the Milky Way, laying the foundation for further high-resolution imaging and spectral verification., Comment: 17 pages, 16 figures; Accepted by The Astronomical Journal

Utilizing high-cadence and continuous g- and r-band data over three nights acquired from the 3.6-meter Canada France Hawaii Telescope (CFHT) aimed to find short-duration microlensing events, we conduct a systematic search for variables, transients, and asteroids across a $\sim1^\circ$ field of view of the Andromeda Galaxy (M 31). We present a catalog of 5859 variable stars, yielding the most extensive compilation of short-period variable sources of M 31. We also detected 19 flares, predominantly associated with foreground M dwarfs in the Milky Way. In addition, we discovered 17 previously unknown asteroid candidates, and we subsequently reported them to the Minor Planet Center. Lastly, we report a microlensing event candidate C-ML-1 and present a preliminary analysis.

The upcoming Chinese Space Station Telescope (CSST) slitless spectroscopic survey poses a challenge of flux calibration, which requires a large number of flux-standard stars. In this work, we design an uncertainty-aware residual attention network, the UaRA-net, to derive the CSST SEDs with a resolution of R = 200 over the wavelength range of 2500-10000 \AA using LAMOST normalized spectra with a resolution of R = 2000 over the wavelength range of 4000-7000 \AA. With the special structure and training strategy, the proposed model can not only provide accurate predictions of SEDs but also their corresponding errors. The precision of the predicted SEDs depends on effective temperature (Teff), wavelength, and the LAMOST spectral signal-to-noise ratios (SNRs), particularly in the GU band. For stars with Teff = 6000 K, the typical SED precisions in the GU band are 4.2%, 2.1%, and 1.5% at SNR values of 20, 40, and 80, respectively. As Teff increases to 8000 K, the precision increases to 1.2%, 0.6%, and 0.5%, respectively. The precision is higher at redder wavelengths. In the GI band, the typical SED precisions for stars with Teff = 6000 K increase to 0.3%, 0.1%, and 0.1% at SNR values of 20, 40, and 80, respectively. We further verify our model using the empirical spectra of the MILES and find good performance. The proposed method will open up new possibilities for optimal utilization of slitless spectra of the CSST and other surveys., Comment: 20 pages, 15 figures, accepted by ApJS

By combining spectra from the CALSPEC and NGSL, as well as spectroscopic data from the LAMOST Data Release 7 (DR7), we have analyzed and corrected the systematic errors of the Gaia DR3 BP/RP (XP) spectra. The errors depend on the normalized spectral energy distribution (simplified by two independent ``colors'') and $G$ magnitude. Our corrections are applicable in the range of approximately $-0.5

Using integral field spectroscopy from MaNGA, we study the resolved microstructures in a shocked region in Criss Cross Nebula (CCN), with an unprecedentedly high resolution of $\lesssim$1000 AU. We measure surface brightness maps for 34 emission lines, which can be broadly divided into three categories: (1) the [OIII] $\lambda$5007-like group including seven high-ionization lines and two [OII] auroral lines which uniformly present a remarkable lane structure, (2) the H$\alpha$ $\lambda$6563-like group including 23 low-ionization or recombination lines which present a clump-like structure, and (3) [OII] $\lambda$3726 and [OII] $\lambda$3729 showing high densities at both the [OIII] $\lambda$5007 lane and the H$\alpha$ clump. We use these measurements to constrain resolved shock models implemented in MAPPINGS V. We find our data can be reasonably well-fitted by a model which includes a plane-parallel shock with a velocity of $133\pm5$ km/s, plus an isotropic two-dimensional Gaussian component which is likely another clump of gas ionized by photons from the shocked region, and a constant background. We compare the electron density and temperature profiles as predicted by our model with those calculated using observed emission line ratios. We find different line ratios to provide inconsistent temperature maps, and the discrepancies can be attributed to observational effects caused by limited spatial resolution and projection of the shock geometry, as well as contamination of the additional Gaussian component. Implications on shock properties and perspectives on future IFS-based studies of CCN are discussed., Comment: Accepted for publication in ApJ, 21 pages, 15 figures

We combine photometric data from GALEX GR6+7 AIS and Gaia EDR3 with stellar parameters from the SAGA and PASTEL catalogs to construct high-quality training samples for dwarfs ($\rm 0.4< BP-RP<1.6$) and giants ($\rm 0.6< BP-RP <1.6$). We apply careful reddening corrections using empirical temperature- and extinction-dependent extinction coefficients. Using the two samples, we establish a relationship between stellar loci (NUV$-$BP vs. BP$-$RP colors), metallicity, and $\rm M_G$. 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, and $\rm M_G$. Thanks to the strong metallicity dependence in the GALEX NUV-band, our models enable a typical photometric-metallicity precision of approximately $\sigma_{\rm [Fe/H]}$ = 0.11 dex for dwarfs and $\sigma_{\rm [Fe/H]}$ = 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 Gaia and GALEX 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., Comment: 24 pages, 19 figures, accepted by ApJS

As early-type stars with a rotation speed close to their critical velocity, Be stars experience an event called the Be phenomenon. The material in their equator is ejected into outside space during the Be phenomenon and forms a circumstellar disk. The mechanism triggering these events remains poorly understood, and observations of these events are limited because the duration of these events ranges from months to years. Long-term epoch photometry in the infrared bands is expected to be ideal for detecting Be phenomena because the brightness variation is larger, and the effect of interstellar extinction is weaker as well. We conducted a systematic search for Be phenomena among Milky Way OBA stars in the mid-infrared. We examined the brightness and colour variations of known classical Be stars using the WISE W1 and W2 photometry bands to quantify their characteristics. Subsequently, we established a set of criteria to identify similar photometric variations in a large sample of OBA stars. We found 916 OBA stars that show Be phenomena in the past 13 years, 736 of which are newly discovered. The peak-to-peak variations in magnitude and colour were found to be correlated, indicating that a decretion disk is common. The increase in colour was observed to be strongly correlated with the emission of the H-alpha line, providing further evidence of the association with circumstellar disks. The brightness variation of a star with Be phenomena can be up to 1.5 mag, and the colour variations can be up to 0.4 mag. The median durations for the disk build-up and decay phases are 474 and 524 days, respectively (durations shorter than 180 days are not sampled). The search for Be phenomena in the WISE bands greatly enlarges the number of stars showing disk variation, and it enables multi-band photometry analysis of these events with the help of current and future optical photometry surveys., Comment: 14 pages, 16 figures, 5 tables, accepted for publication in A&A

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 SDSS/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] $\leq$ --2) and extremely metal-poor (EMP; [Fe/H] $\leq$ --3) stars. Our analysis is based on an initial sample of $\sim11.5$ 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 $\sim$5.86 million stars in the combined SMSS/SAGES sample. We employ two techniques that, depending on the method, identify between 876 and 1,476 VMP stars (6.9%-11.7% of all VMP stars) and between 40 and 59 EMP stars (12.4%-18.3% of all EMP stars) that appear to be members of the Galactic disk system on highly prograde orbits (v$_{\phi} > 150$ km/s). The total number of candidate VMP/EMP disk-like stars is 1,496, the majority of which have low orbital eccentricities, ecc $\le 0.4$; many have ecc $\le 0.2$. The large fractions of VMP/EMP stars associated with the Milky Way disk system strongly suggest the presence of an early forming ``primordial" disk., Comment: It is now accepted to the ApJS

We employ the corrected Gaia Early Data Release 3 (EDR3) 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 validated the J-PLUS DR3 photometry, and uncovered significant systematic errors: up to 15 mmag in the results of Stellar Locus (SL) method, and up to 10 mmag mainly caused by magnitude-, color-, and extinction-dependent errors of the Gaia XP spectra with the Gaia BP/RP (XP) Synthetic Photometry (XPSP) method. We have also further developed the XPSP method using the corrected Gaia XP spectra by Huang et al. (2023) and applied it to the J-PLUS DR3 photometry. This resulted in an agreement of 1-5 mmag with the SCR method, and a two-fold 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 tiles outside this footprint relying on the improved XPSP method. The re-calibrated J-PLUS DR3 photometric data establishes a solid data foundation for conducting research that depends on high-precision photometric calibration., Comment: ApJS accepted; 21 papes; 20 figures, see main results in Figures 5 and 12

We present a comprehensive re-calibration of medium- and broad-band 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, the Stellar Color Regression (SCR) method with corrected Gaia EDR3 photometric data and spectroscopic data from LAMOST DR7. 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 DR4 photometric data. A comparison between the XPSP and SCR methods reveals minor differences in zero-point offsets, typically within the range of 1 to 6 mmag, indicating the accuracy of the re-calibration, and a two- to three-fold improvement in the zero-point precision. During this process, we also verified and corrected for the systematic errors related to CCD position. The corrected S-PLUS DR4 photometric data will provide a solid data foundation for conducting scientific research that relies on high-calibration precision. 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 sub-surveys., Comment: 15 pages, 15 figures, submitted, see main results in Figures 4 and 8

The total-to-selective extinction ratio, Rv, is a key parameter for tracing the properties of interstellar dust, as it directly determines the variation of the extinction curve with wavelength. By utilizing accurate color excess measurements from the optical to the mid-infrared range, we have derived Rv values for approximately 3 million stars from the LAMOST data release 7 (DR7) using a forward modeling technique. This extensive dataset enables us to construct a comprehensive two-dimensional Rv map of the Milky Way within the LAMOST footprint at a spatial resolution of ~27.5arcmin. Based on reliable sightlines of E(B-V) > 0.1, we find that Rv exhibits a Gaussian distribution centered around 3.25 with a standard deviation of 0.25. The spatial variability of Rv in the Galactic disk exhibits a wide range, spanning from small scales within individual molecular clouds to large scales up to kiloparsecs. A striking correlation is observed between the distribution of Rv and molecular clouds. Notably, we observe lower Rv values within the regions of nearby molecular clouds compared to their surrounding areas. Furthermore, we have investigated the relationships between Rv and various parameters, including dust temperature, dust emissivity spectral index, column density of atomic and molecular hydrogen, as well as their ratios and the gas-to-dust ratio. We find that these relationships vary with the level of extinction. These analyses provide new insights into the properties and evolution of dust grains in diverse interstellar environments and also hold significant importance for achieving accurate extinction corrections., Comment: 16 pages, 12 figures. Accepted for publication in the Astrophysical Journal Supplement Series

In this work, we perform the re-calibration of PS1 photometry by correcting for position-dependent systematic errors using the spectroscopy-based Stellar Color Regression method (SCR), the photometry-based SCR method (SCR$'$), and the Gaia XP synthetic photometry method (XPSP). We confirm the significant large-scale and small-scale spatial variation of magnitude offsets for all the $grizy$ filters. We show that the PS1 photometric calibration precisions in the $grizy$ filters are around 5--7\,mmag when averaged over 14$'$ regions. We note a much larger calibration error up to 0.04 mag in the Galactic plane, which is probably caused by the systematic errors of the PS1 magnitudes in crowded fields. The results of the three methods are consistent with each other within 1--2\,mmag or better for all the filters. We provide two-dimensional maps and a python package ({\url{https://doi.org/10.12149/101283}}) to correct for position-dependent magnitude offsets of PS1, which can be used for high-precision investigations and as a reference to calibrate other surveys., Comment: 14 pages, 18 figures, ApJS accepted, see main results in Figures 11 and 12

Gaia DR3 mission has identified and provided about 440,000 binary systems with orbital solutions, offering a valuable resource for searching binaries including a compact component. By combining the Gaia DR3 data with radial velocities (RVs) from the LAMOST spectroscopic survey, we identify three wide binaries possibly containing a compact object. For two of these sources with a main-sequence companion, no obvious excess is observed in the blue/red band of the Gaia DR3 XP spectra, and the LAMOST medium-resolution spectra exhibit clear single-lined features. The absence of an additional component from spectral disentangling analysis further suggests the presence of compact objects within these systems. On the other hand, the visible star of the third source is a stripped giant star. In contrast to most binaries including stripped stars, no emission line is detected in the optical spectra. The unseen star could potentially be a massive white dwarf or neutron star, but the possibility of an F-type dwarf star scenario cannot be ruled out. An examination of about ten binaries containing white dwarfs or neutron stars using both kinematic and chemical methods suggest most of these systems are located in the thin disk of the Milky Way., Comment: 20 pages, 13 figures, accepted by APJ

In this paper, a total of approximately 2.6 million dwarfs were constructed as standard stars, with an accuracy of about 0.01-0.02 mag for each band, by combining spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope Data Release 7, photometric data from the corrected Gaia Early Data Release 3, and photometric metallicities. Using the spectroscopy based stellar color regression method (SCR method) and the photometric-based SCR method (SCR' method), we performed the relative calibration of the Nanshan One-meter Wide-field Telescope imaging data. Based on the corrected Pan-STARRS DR1 photometry, the absolute calibration was also performed. In the photometric calibration process, we analyzed the dependence of the calibration zero points on different images (observation time), different gates of the CCD detector, and different CCD positions. We found that the stellar flat and the relative gain between different gates depend on time. The amplitude of gain variation in three channels is approximately 0.5%-0.7% relative to the other channel, with a maximum value of 4%. In addition, significant spatial variations of the stellar flat fitting residual are found and corrected. Using repeated sources in the adjacent images, we checked and discovered internal consistency of about 1-2 mmag in all the filters. Using the PS1 magnitudes synthesized by Gaia DR3 BP/RP spectra by the synthetic photometry method, we found that the photometric calibration uniformity is about 1-2 mmag for all the bands, at a spatial resolution of 1.3 degree. A detailed comparison between the spectroscopy-based SCR and photometric-based SCR method magnitude offsets was performed, and we achieved an internal consistency precision of about 2 mmag or better with resolutions of 1.3 degree for all the filters. Which is mainly from the position-dependent errors of the E(B-V) used in SCR' method., Comment: 15 pages in Chinese language, 8 figures, Chinese Science Bulletin accepted and published online (https://www.sciengine.com/CSB/doi/10.1360/TB-2023-0052), see main results in Figures 6, 7 and 8

We found 50 new globular cluster (GC) candidates around M\,31 with Gaia Early Data Release 3 (EDR3), with the help from Pan-STARRS1 DR1 magnitudes and Pan-Andromeda Archaeological Survey (PAndAS) images. Based on the latest Revised Bologna Catalog and \textit{simbad}, we trained 2 Random Forest (RF) classifiers, the first one to distinguish extended sources from point sources and the second one to further select GCs from extended sources. From 1.85 million sources of $16^m{<}g{<}19.5^m$ and within a large area of $\sim$392\,deg$^2$ around M\,31, we selected 20,658 extended sources and 1,934 initial GC candidates. After visual inspection of the PAndAS images to eliminate the contamination of non-cluster sources, particularly galaxies, we finally got 50 candidates. These candidates are divided into 3 types (\textbf{a}, \textbf{b}, \textbf{c}) according to their projected distance $D$ to the center of M\,31 and their probability to be a true GC, $P_{GC}$, which is calculated by our second RF classifier. Among these candidates, 14 are found to be associated (in projection) with the large-scale structures within the halo of M\,31. We also provided several simple parameter criteria for selecting extended sources effectively from the Gaia EDR3, which can reach a completeness of 92.1\% with a contamination fraction lower than 10\%.

The Stellar Abundances and Galactic Evolution Survey (SAGES) of the northern sky is a specifically-designed multi-band photometric survey aiming to provide reliable stellar parameters with accuracy comparable to those from low-resolution optical spectra. It was carried out with the 2.3-m Bok telescope of Steward Observatory and three other telescopes. The observations in the $u_s$ and $v_s$ passband produced over 36,092 frames of images in total, covering a sky area of $\sim9960$ degree$^2$. The median survey completeness of all observing fields for the two bands are of $u_{\rm s}=20.4$ mag and $v_s=20.3$ mag, respectively, while the limiting magnitudes with signal-to-noise ratio (S/N) of 100 are $u_s\sim17$ mag and $v_s\sim18$ mag, correspondingly. We combined our catalog with the data release 1 (DR1) of the first of Panoramic Survey Telescope And Rapid Response System (Pan-STARRS1, PS1) catalog, and obtained a total of 48,553,987 sources which have at least one photometric measurement in each of the SAGES $u_s$ and $v_s$ and PS1 $grizy$ passbands, which is the DR1 of SAGES and it will be released in our paper. We compare our $gri$ point-source photometry with those of PS1 and found an RMS scatter of $\sim2$% in difference of PS1 and SAGES for the same band. We estimated an internal photometric precision of SAGES to be on the order of $\sim1$%. Astrometric precision is better than $0^{\prime\prime}.2$ based on comparison with the DR1 of Gaia mission. In this paper, we also describe the final end-user database, and provide some science applications., Comment: 49 pages, 21 figures, 5 table, accepted for publication in ApJS

Stellar chemical abundances are crucial and fundamental in astrophysics. However, they could suffer from substantial systematic errors according to several investigations but still lack calibrations in bulk. By using Gaia wide binaries, we find the temperature-dependent bias between the two binary components for [Fe/H] and [alpha/Fe] measurements from the LAMOST low-resolution spectra and Gaia RVS spectra. At Teff=4000 K, the LAMOST [Fe/H] is significantly underestimated by approximately 0.4 dex, compared with its typical uncertainty of 0.1 dex. Its [alpha/Fe] is overestimated by about 0.2 dex. For Gaia, the underestimation of [M/H] and overestimation of [alpha/Fe] becomes pronounced near 7000 K with smaller magnitudes. We perform an internal calibration by minimizing the differences between binary components and provide the correction curves. After corrections, the standard deviations of the residuals compared to the PASTEL catalog decrease from about 0.045/0.1 to 0.02/0.043 for LAMOST and Gaia, respectively. The chemical homogeneity of the open cluster M 44 is also improved by a factor of two. We stress that the underestimation of [Fe/H] could lead to an overestimation of binary fractions when selecting binary stars by the excess of luminosity. The method of this work could be applied to other data-sets in the future. Our results will benefit statistic studies that use LAMOST and Gaia samples with a wide temperature range., Comment: 13 pages, 7 figure, ApJ accepted, comments are welcome

We investigate the radial metallicity gradients and azimuthal metallicity distributions on the Galactocentric $X$--$Y$ plane using mono-temperature stellar populations selected from LAMOST MRS young stellar sample. The estimated radial metallicity gradient ranges from $-$0.015\,dex/kpc to $-$0.07\,dex/kpc, which decreases as effective temperature decreases (or stellar age increases) at $7500 < T_{\rm eff} < 12500$\,K ($\tau < $1.5 Gyr). The azimuthal metallicity excess (metallicity after subtracting radial metallicity gradient, $\Delta$\,[M/H]) distributions exhibit inhomogeneities with dispersions of 0.04\,dex to 0.07\,dex, which decrease as effective temperature decreases. We also identify five potential metal-poor substructures with large metallicity excess dispersions. The metallicity excess distributions of these five metal-poor substructures suggest that they contain a larger fraction of metal-poor stars compared to other control samples. These metal-poor substructures may be associated with high-velocity clouds that infall into the Galactic disk from the Galactic halo, which are not quickly well-mixed with the pre-existing ISM of the Galactic disk. As a result, these high-velocity clouds produce some metal-poor stars and the observed metal-poor substructures. The variations of metallicity inhomogeneities with different stellar populations indicate that high-velocity clouds are not well mixed with the pre-existing Galactic disk ISM within 0.3\,Gyr., Comment: 14 pages, 12 figures, Accepted for publication in A&A

We have obtained accurate dust reddening from far-ultraviolet (UV) to the mid-infrared (IR) for up to 5 million stars by the star-pair algorithm based on LAMOST stellar parameters along with GALEX, Pan-STARRS 1, Gaia, SDSS, 2MASS, and WISE photometric data. The typical errors are between 0.01-0.03 mag for most colors. We derived the empirical reddening coefficients for 21 colors both in the traditional (single valued) way and as a function of Teff and E(B-V) by using the largest samples of accurate reddening measurements, together with the extinction values from Schlegel et al. The corresponding extinction coefficients have also been obtained. The results are compared with model predictions and generally in good agreement. Comparisons with measurements in the literature show that the Teff- and E(B-V)-dependent coefficients explain the discrepancies between different measurements naturally, i.e., using sample stars of different temperatures and reddening. Our coefficients are mostly valid in the extinction range of 0-0.5 mag and the temperature range of 4000-10000 K. We recommend that the new Teff and E(B-V) dependent reddening and extinction coefficients should be used in the future. A Python package is also provided for the usage of the coefficient, Comment: 21 pages, 9 figures, 4 table (including appendix). Published in the Astrophysical Journal Supplement Series

We employ Gaia, 2MASS, and ALLWISE photometry, as well as astrometric data from Gaia, to search for relatively bright very metal-poor ([Fe/H] $< -2.0$; VMP) giant star candidates using three different criteria: 1) our derived Gaia photometric metallicities, 2) the lack of stellar molecular absorption near 4.6 microns, and 3) their high tangential velocities. With different combinations of these criteria, we have identified six samples of candidates with $G <$ 15: the Gold sample (24,304 candidates), the Silver GW sample (40,157 candidates), the Silver GK sample (120,452 candidates), the Bronze G sample (291,690 candidates), the Bronze WK sample (68,526 candidates), and the Low $b$ sample (4,645 candidates). The Low $b$ sample applies to sources with low Galactic latitude, $|b| < 10^\circ$, while the others are for sources with $|b| > 10^\circ$. By cross-matching with results derived from medium-resolution ($R \sim$ 1800) from LAMOST DR8, we establish that the success rate for identifying VMP stars is 60.1$\%$ for the Gold sample, 39.2$\%$ for the Silver GW sample, 41.3$\%$ for the Silver GK sample, 15.4$\%$ for the Bronze G sample, 31.7$\%$ for the Bronze WK sample, and 16.6$\%$ for the Low $b$ sample, respectively. An additional strict cut on the quality parameter $RUWE < 1.1$ can further increase the success rate of the Silver GW, Silver GK, and Bronze G samples to 46.9$\%$, 51.6$\%$, and 29.3$\%$, respectively. Our samples provide valuable targets for high-resolution follow-up spectroscopic observations, and are made publicly available., Comment: 15 pages, 9 figures, 4 tables, accepted for publication in ApJS, data is available at https://doi.org/10.12149/101160

We propose to develop a wide-field and ultra-high-precision photometric survey mission, temporarily named "Earth 2.0 (ET)". This mission is designed to measure, for the first time, the occurrence rate and the orbital distributions of Earth-sized planets. ET consists of seven 30cm telescopes, to be launched to the Earth-Sun's L2 point. Six of these are transit telescopes with a field of view of 500 square degrees. Staring in the direction that encompasses the original Kepler field for four continuous years, this monitoring will return tens of thousands of transiting planets, including the elusive Earth twins orbiting solar-type stars. The seventh telescope is a 30cm microlensing telescope that will monitor an area of 4 square degrees toward the galactic bulge. This, combined with simultaneous ground-based KMTNet observations, will measure masses for hundreds of long-period and free-floating planets. Together, the transit and the microlensing telescopes will revolutionize our understandings of terrestrial planets across a large swath of orbital distances and free space. In addition, the survey data will also facilitate studies in the fields of asteroseismology, Galactic archeology, time-domain sciences, and black holes in binaries., Comment: 116 pages,79 figures

M dwarfs are the dominating type of stars in the solar neighbourhood. They serve as excellent tracers for the study of the distribution and properties of the nearby interstellar dust. In this work, we aim to obtain high accuracy reddening values of M dwarf stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 8 (DR8). Combining the LAMOST spectra with the high-quality optical photometry from the Gaia Early Data Release 3 (Gaia EDR3), we have estimated the reddening values $E(G_{\rm BP}-G_{\rm RP})$ of 641,426 M dwarfs with the machine-learning algorithm Random Forest regression. The typical reddening uncertainty is only 0.03 mag in $E(G_{\rm BP}-G_{\rm RP})$. We have obtained the reddening coefficient $R_{(G_{\rm BP}-G_{\rm RP})}$, which is a function of the stellar intrinsic colour $(G_{\rm BP}-G_{\rm RP})_0$ and reddening value $E(B-V)$. The values of $E(B-V)$ are also provided for the individual stars in our catalogue. Our resultant high accuracy reddening values of M dwarfs, combined with the Gaia parallaxes, will be very powerful to map the fine structures of the dust in the solar neighbourhood., Comment: 8 pages, 8 figures, accepted for publication in MNRAS

Uniform and accurate photometric calibration plays an important role in the current and next-generation wide-field imaging surveys. Herein, we review the modern photometric calibration methods, including the classic standard star method, "hardware/observation-driven" methods (such as the Ubercalibration, Hypercalibration, and Forward Global Calibration Methods), and "software/physics-driven" methods (e.g., the Stellar Locus Regression, Stellar Locus, and Stellar Color Regression Methods). Further, we discuss their advantages, limitations, and future developments toward millimagnitude precision calibration., Comment: Scientia Sinica Physica, Mechanica & Astronomica accepted, in Chinese language

The metallicity dependence of the wide binary fraction (WBF) is critical for studying the formation of wide binaries. While controversial results have been found in recent years. Here we combine the wide binary catalog recognized from Gaia EDR3 and stellar parameters from LAMOST to investigate this topic. Taking bias of the stellar temperature at given separations into account, we find that the relationship between the WBF and metallicity depends on temperature for the thin-disk at s > 200 AU. It changes from negative to positive as the temperature increases from 4000 K to 7500 K. This temperature/mass dependence is not seen for the thick-disk. Besides, the general tendency between the WBF and metallicity varies with the separation, consistent with previous results. It shows anti-correlation at small separations, s < 200 AU for the thin-disk and s < 600 AU for the thick-disk. Then it becomes an "arcuate" shape at larger separations (hundreds to thousands of AU), peaking at [Fe/H] ~ 0.1 for the thin-disk and [Fe/H] ~ -0.5 for the thick disk. Finally it becomes roughly flat for the thin-disk at 1000 < s < 10000 AU. Our work provides new observational evidences for theoretical studies on binary formation and evolution., Comment: 14 pages, 9 figures, ApJ accepted. Comments are welcome

Context. Stellar parameters are among the most important characteristics in studies of stars, which are based on atmosphere models in traditional methods. However, time cost and brightness limits restrain the efficiency of spectral observations. The J-PLUS is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools to efficiently analyse large data sets, such as the one from J-PLUS, and enable us to expand the research domain to stellar parameters. Aims. The main goal of this study is to construct a SVR algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. Methods. The training data for the parameters regressions is featured with 12-waveband photometry from J-PLUS, and is cross-identified with spectrum-based catalogs. These catalogs are from the LAMOST, the APOGEE, and the SEGUE. We then label them with the stellar effective temperature, the surface gravity and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach in order to fully take into account the uncertainties of both the magnitudes and stellar parameters. The method utilizes more than two hundred models to apply the uncertainty analysis. Results. We present a catalog of 2,493,424 stars with the Root Mean Square Error of 160K in the effective temperature regression, 0.35 in the surface gravity regression and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods., Comment: 18 pages, 10 figures, accepted by AA

Precise correction of dust reddening is fundamental to obtain the intrinsic parameters of celestial objects. The Schlegel et al. (SFD) and the Planck 2D extinction maps are widely used for the reddening correction. In this work, using accurate reddening determinations of about two million stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) data release 5 (DR5) and Gaia DR2, we check and calibrate the SFD and Planck maps in the middle and high Galactic latitudes. The maps show similar precision in reddening correction. We find small yet significant spatially dependent biases for the four maps, which are similar between the SFD and Planck2014-R maps, and between the Planck2014-Tau and Planck2019-Tau maps. The biases show a clear dependence on the dust temperature and extinction for the SFD and Planck2014-R maps. While those of the Planck2014-Tau and Planck2019-Tau maps have a weak dependence on the dust temperature, they both strongly depend on the dust spectral index. Finally, we present corrections of the SFD and Planck extinction maps within the LAMOST footprint, along with empirical relations for corrections outside the LAMOST footprint. Our results provide important clues for the further improvement of the Galactic all-sky extinction maps and lay an significant foundation for the accurate extinction correction in the era of precision astronomy., Comment: 25 pages, 18 figures, accepted for publication in ApJS. For associated .fits file and public codes, please see \url{http://paperdata.china-vo.org/Dustmaps-correction/extinction-maps-correction.zip} and \url{https://github.com/qy-sunyang/Extinction-Maps-Correction}

As a completely independent method, the measurement of time delay of strongly lensed quasars (TDSL) are crucial to resolve the Hubble tension. Extensive monitoring is required but so far limited to a small sample of strongly lensed quasars. Together with several partner institutes, Beijing Normal University is constructing a 1.93m reflector telescope at the Muztagh-Ata site in west China, which has the world class observing conditions. The telescope will be equipped with both a three-channel imager/photometer which covers $3500-11000$ Angstrom wavelength band, and a low-medium resolution ($\lambda/\delta\lambda=500/2000/7500$) spectrograph. In this paper, we investigate the capability of Muztagh-Ata 1.93m telescope in measuring time delays of strongly lensed quasars. We generate mock strongly lensed quasar systems and light curves with microlensing effects based on five known strongly lensed quasars, i.e., RX J1131-1231, HE 0435-1223, PG 1115+080, WFI 2033-4723 and SDSS 1206+4332. In particular, RX J1131-1231 is generated with lens modeling in this work. Due to lack of enough information, we simulate the other 4 systems with the public data without lens modeling. According to simulations, for RX J1131-like systems (wide variation in time delay between images) the TDSL measurement can be achieved with the precision about $\Delta t=0.5$ day with 4 seasons campaign length and 1 day cadence. This accuracy is comparable to the up-coming TDCOSMO project. And it would be better when the campaign length keeps longer and with high cadence. As a result, the capability of Muztagh-Ata 1.93m telescope allows it to join the network of TDSL observatories. It will enrich the database for strongly lensed quasar observations and make more precise measurements of time delays, especially considering the unique coordinate of the site., Comment: 17 pages, 15 figures

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), also known as the Guoshoujing Telescope, is a major national scientific facility for astronomical research located in Xinglong, China. Beginning with a pilot survey in 2011, LAMOST has been surveying the night sky for more than 10 years. The LAMOST survey covers various objects in the Universe, from normal stars to peculiar ones, from the Milky Way to other galaxies, and from stellar black holes and their companions to quasars that ignite ancient galaxies. Until the latest data release 8, the LAMOST survey has released spectra for more than 10 million stars, ~220,000 galaxies, and ~71,000 quasars. With this largest celestial spectra database ever constructed, LAMOST has helped astronomers to deepen their understanding of the Universe, especially for our Milky Way galaxy and the millions of stars within it. In this article, we briefly review the characteristics, observations, and scientific achievements of LAMOST. In particular, we show how astrophysical knowledge about the Milky Way has been improved by LAMOST data., Comment: 16 pages, 10 figures. Published by The Innovation

As one of the best ground-based photometric dataset, Pan-STARRS1 (PS1) has been widely used as the reference to calibrate other surveys. In this work, we present an independent validation and re-calibration of the PS1 photometry using spectroscopic data from the LAMOST DR7 and photometric data from the corrected Gaia EDR3 with the Stellar Color Regression (SCR) method. Using per band typically a total of 1.5 million LAMOST-PS1-Gaia stars as standards, we show that the PS1 photometric calibration precisions in the $grizy$ filters are around $4\sim 5$ mmag when averaged over $20'$ regions. However, significant large- and small-scale spatial variation of magnitude offset, up to over 1 per cent, probably caused by the calibration errors in the PS1, are found for all the $grizy$ filters. The calibration errors in different filters are un-correlated, and are slightly larger for the $g$ and $y$ filters. We also detect moderate magnitude-dependent errors (0.005, 0.005, 0.005, 0.004, 0.003 mag per magnitude in the 14 -- 17 magnitude range for the $grizy$ filters, respectively) in the PS1 photometry by comparing with the Gaia EDR3 and other catalogs. The errors are likely caused by the systematic uncertainties in the PSF magnitudes. We provide two-dimensional maps to correct for such magnitude offsets in the LAMOST footprint at different spatial resolutions from $20'$ to $160'$. The results demonstrate the power of the SCR method in improving the calibration precision of wide-field surveys when combined with the LAMOST spectroscopy and Gaia photometry., Comment: 12 pages, 15 figures, AJ accepted, see main results in Figures 7 and 14

We present a value-added catalog containing stellar parameters estimated from 7.10 million low-resolution spectra for 5.16 million unique stars with spectral signal-to-noise ratios (SNRs) higher than 10 obtained by the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) Galactic spectroscopic surveys. The catalog presents values of stellar atmospheric parameters (effective temperature $T_{\mathrm{eff}}$, surface gravity $\log g$, metallicity [Fe/H]/[M/H]), $\alpha$-element to metal abundance ratio [$\alpha$/M], carbon and nitrogen to iron abundance ratios [C/Fe] and [N/Fe] and 14 bands' absolute magnitudes deduced from LAMOST spectra using the method of neural network. The spectro-photometric distances of those stars are also provided based on the distance modulus. For stars with spectral SNRs larger than 50, precisions of $T_{\mathrm{eff}}$, $\log g$, [Fe/H], [M/H], [C/Fe], [N/Fe] and [$\alpha$/M] are 85\,K, 0.098\,dex, 0.05\,dex, 0.05\,dex, 0.052\,dex, 0.082\,dex and 0.027\,dex, respectively. The errors of 14 band's absolute magnitudes are 0.16--0.22\,mag for stars with spectral SNRs larger than 50. The spectro-photometric distance is accurate to 8.5\% for stars with spectral SNRs larger than 50, and is more accurate than geometrical distance for stars with distance larger than 2.0\,kpc. Our estimates of [Fe/H] are reliable down to [Fe/H] $\sim -3.5$\,dex, significantly better than previous results. The catalog provide 26,868 unique very metal poor star candidates ([Fe/H] $\leq -2.0$). The catalog would be a valuable data set to study the structure and evolution of the Galaxy, especially the solar-neighbourhood and the outer disc., Comment: 34 pages, 30 figures, 3 tables, accepted for publication in ApJS

We have studied the zero-point offset of Gaia early Data Release 3 (EDR3) parallaxes based on a sample of 0.3 million giant stars built from the LAMOST data with distance accuracy better than 8.5\%. The official parallax zero-point corrections largely reduce the global offset in the Gaia EDR3 parallaxes: the global parallax offsets are $-$27.9 $\mu$as and $-$26.5 $\mu$as (before correction) and $+$2.6 $\mu$as and $+$2.9 $\mu$as (after correction) for the five- and six-parameter solutions, respectively. The bias of the raw parallax measurements is significantly dependent on the $G$ magnitudes, spectral colors, and positions of stars. The official parallax zero-point corrections could reduce parallax bias patterns with $G$ magnitudes, while could not fully account the patterns in the spaces of the spectral colors and positions. In the current paper, a spatially dependent parallax zero-point correction model for Gaia EDR3 five-parameter solution in the LAMOST footprint is firstly provided with the advantage of huge number of stars in our sample., Comment: 9 pages, 6 figures, 1 table, accepted for publication in AJ

By combining spectroscopic data from the LAMOST DR7, SDSS DR12, and corrected photometric data from the Gaia EDR3, we apply the Stellar Color Regression (SCR; Yuan et al. 2015a) method to recalibrate the SDSS Stripe 82 standard stars catalog of Ivezi\'c et al. (2007). With a total number of about 30,000 spectroscopically targeted stars, we have mapped out the relatively large and strongly correlated photometric zero-point errors present in the catalog, $\sim$2.5 per cent in the $u$ band and $\sim$ 1 per cent in the $griz$ bands. Our study also confirms some small but significant magnitude dependence errors in the $z$ band for some charge-coupled devices. Various tests show that we have achieved an internal precision of about 5 mmag in the $u$ band and about 2 mmag in the $griz$ bands, which is about 5 times better than previous results. We also apply the method to the latest version of the catalog (V4.2; Thanjavur et al. 2021), and find modest systematic calibration errors up to $\sim$ 1 per cent along the R.A. direction and smaller errors along the Dec. direction. The results demonstrate the power of the SCR method when combining spectroscopic data and Gaia photometry in breaking the 1 percent precision barrier of ground-based photometric surveys. Our work paves the way for the re-calibration of the whole SDSS photometric survey and has important implications for the calibration of future surveys. Future implementations and improvements of the SCR method under different situations are also discussed., Comment: 21 pages, 20 figures, 9 tables, ApJS in press

Context. The Javalambre Photometric Local Universe Survey (J-PLUS) has obtained precise photometry in twelve specially designed filters for large numbers of Galactic stars. Deriving their precise stellar atmospheric parameters and individual elemental abundances is crucial for studies of Galactic structure, and the assembly history and chemical evolution of our Galaxy. Aims. Our goal is to estimate not only stellar parameters (effective temperature, Teff, surface gravity, log g, and metallicity, [Fe/H]), but also [{\alpha}/Fe] and four elemental abundances ([C/Fe], [N/Fe], [Mg/Fe], and [Ca/Fe]) using data from J-PLUS DR1. Methods. By combining recalibrated photometric data from J-PLUS DR1, Gaia DR2, and spectroscopic labels from LAMOST, we design and train a set of cost-sensitive neural networks, the CSNet, to learn the non-linear mapping from stellar colors to their labels. Results. We have achieved precisions of {\delta}Teff {\sim}55K, {\delta}logg{\sim}0.15dex, and {\delta}[Fe/H]{\sim}0.07dex, respectively, over a wide range of temperature, surface gravity, and metallicity. The uncertainties of the abundance estimates for [{\alpha}/Fe] and the four individual elements are in the range 0.04-0.08 dex. We compare our parameter and abundance estimates with those from other spectroscopic catalogs such as APOGEE and GALAH, and find an overall good agreement. Conclusions. Our results demonstrate the potential of well-designed, high-quality photometric data for determinations of stellar parameters as well as individual elemental abundances. Applying the method to J-PLUS DR1, we have obtained the aforementioned parameters for about two million stars, providing an outstanding data set for chemo-dynamic analyses of the Milky Way. The catalog of the estimated parameters is publicly accessible., Comment: 30 pages, 26 figures, 3 tables, accepted by A&A

We combine LAMOST DR7 spectroscopic data and Gaia EDR3 photometric data to construct high-quality giant (0.7 $< (BP-RP) <$ 1.4) and dwarf (0.5 $< (BP-RP) < $ 1.5) samples in the high Galactic latitude region, with precise corrections for magnitude-dependent systematic errors in the Gaia photometry and careful reddening corrections using empirically determined color- and reddening-dependent coefficients. We use the two samples to build metallicity-dependent stellar loci of Gaia colors for giants and dwarfs, respectively. For a given $(BP-RP)$ color, a one dex change in [Fe/H] results in about a 5 mmag change in $(BP-G)$ color for solar-type stars. These relations are used to determine metallicity estimates from EDR3 colors. Despite the weak sensitivity, the exquisite data quality of these colors enables a typical precision of about $\delta$\,[Fe/H] = 0.2 dex. Our method is valid for FGK stars with $G \leq 16$, [Fe/H] $\geq -2.5$, and $E(B-V) \leq 0.5$. Stars with fainter $G$ magnitudes, lower metallicities, or larger reddening suffer from higher metallicity uncertainties. With the enormous data volume of Gaia, we have measured metallicity estimates for about 27 million stars with 10 $< G \leq 16$ across almost the entire sky, including over 6 million giants and 20 million dwarfs, which can be used for a number of studies. These include investigations of Galactic formation and evolution, the identification of candidate stars for subsequent high-resolution spectroscopic follow-up, the identification of wide binaries, and to obtain metallicity estimates of stars for asteroseismology and exoplanet research., Comment: 18 pages, 18 figures, 2 tables, accepted for publication in the ApJS, data are publicly available at https://doi.org/10.12149/101081

Context.Identification of new star cluster candidates in M31 is fundamental for the study of the M31 stellar cluster system. The machine-learning method convolutional neural network (CNN) is an efficient algorithm for searching for new M31 star cluster candidates from tens of millions of images from wide-field photometric surveys. Aims.We search for new M31 cluster candidates from the high-quality $g$- and $i$-band images of 21,245,632 sources obtained from the Pan-Andromeda Archaeological Survey (PAndAS) through a CNN. Methods.We collected confirmed M31 clusters and noncluster objects from the literature as our training sample. Accurate double-channel CNNs were constructed and trained using the training samples. We applied the CNN classification models to the PAndAS $g$- and $i$-band images of over 21 million sources to search new M31 cluster candidates. The CNN predictions were finally checked by five experienced human inspectors to obtain high-confidence M31 star cluster candidates. Results.After the inspection, we identified a catalogue of 117 new M31 cluster candidates. Most of the new candidates are young clusters that are located in the M31 disk. Their morphology, colours, and magnitudes are similar to those of the confirmed young disk clusters. We also identified eight globular cluster candidates that are located in the M31 halo and exhibit features similar to those of confirmed halo globular clusters. The projected distances to the M31 centre for three of them are larger than 100\,kpc., Comment: Published in A&A

We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential to identify low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. SPEEM is a tool to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars, using the unique J-PLUS photometric system. The adoption of adequate selection criteria allows the identification of metal-poor star candidates suitable for spectroscopic follow-up. SPEEM consists of a series of machine learning models which uses a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures Teff between 4\,800 K and 9\,000 K; $\log g$ between 1.0 and 4.5, and $-3.1<[Fe/H]<+0.5$. The performance of the pipeline has been tested with a sample of stars observed by the LAMOST survey within the same parameter range. The average differences between the parameters of a sample of stars observed with SEGUE and J-PLUS, which were obtained with the SEGUE Stellar Parameter Pipeline and SPEEM, respectively, are $\Delta Teff\sim 41$ K, $\Delta \log g\sim 0.11$ dex, and $\Delta [Fe/H]\sim 0.09$ dex. A sample of 177 stars have been identified as new candidates with $[Fe/H]<-2.5$ and 11 of them have been observed with the ISIS spectrograph at the William Herschel Telescope. The spectroscopic analysis confirms that $64\%$ of stars have $[Fe/H]<-2.5$, including one new star with $[Fe/H]<-3.0$. SPEEM in combination with the J-PLUS filter system has shown the potential to estimate the stellar atmospheric parameters (Teff, $\log g$, and [Fe/H]). The spectroscopic validation of the candidates shows that SPEEM yields a success rate of $64\%$ on the identification of very metal-poor star candidates with $[Fe/H]<-2.5$., Comment: Accepted for publication in the Astronomy & Astrophysics Journal

In the fourth paper of this series, we present the metallicity-dependent Sloan Digital Sky Survey (SDSS) stellar color loci of red giant stars, using a spectroscopic sample of red giants in the SDSS Stripe 82 region. The stars span a range of 0.55 -- 1.2 mag in color g-i, -0.3 -- -2.5 in metallicity [Fe/H], and have values of surface gravity log g smaller than 3.5 dex. As in the case of main-sequence (MS) stars, the intrinsic widths of loci of red giants are also found to be quite narrow, a few mmag at maximum. There are however systematic differences between the metallicity-dependent stellar loci of red giants and MS stars. The colors of red giants are less sensitive to metallicity than those of MS stars. With good photometry, photometric metallicities of red giants can be reliably determined by fitting the u-g, g-r, r-i, and i-z colors simultaneously to an accuracy of 0.2 -- 0.25 dex, comparable to the precision achievable with low-resolution spectroscopy for a signal-to-noise ratio of 10. By comparing fitting results to the stellar loci of red giants and MS stars, we propose a new technique to discriminate between red giants and MS stars based on the SDSS photometry. The technique achieves completeness of ~ 70 per cent and efficiency of ~ 80 per cent in selecting metal-poor red giant stars of [Fe/H] $\le$ -1.2. It thus provides an important tool to probe the structure and assemblage history of the Galactic halo using red giant stars., Comment: 18 pages, 13 figures. Accepted for publication in Research in Astronomy and Astrophysics

Basing on the large volume \textit{Gaia} Early Data Release 3 and LAMOST Data Release 5 data, we estimate the bias-corrected binary fractions of the field late G and early K dwarfs. A stellar locus outlier method is used in this work, which works well for binaries of various periods and inclination angles with single epoch data. With a well-selected, distance-limited sample of about 90 thousand GK dwarfs covering wide stellar chemical abundances, it enables us to explore the binary fraction variations with different stellar populations. The average binary fraction is 0.42$\pm$0.01 for the whole sample. Thin disk stars are found to have a binary fraction of 0.39$\pm$0.02, thick disk stars own a higher one of 0.49$\pm$0.02, while inner halo stars possibly own the highest binary fraction. For both the thin and thick disk stars, the binary fractions decrease toward higher [Fe/H], [$\alpha$/H], and [M/H] abundances. However, the suppressing impacts of the [Fe/H], [$\alpha$/H], and [M/H] are more significant for the thin disk stars than those for the thick disk stars. For a given [Fe/H], a positive correlation between [$\alpha$/Fe] and the binary fraction is found for the thin disk stars. However, this tendency disappears for the thick disk stars. We suspect that it is likely related to the different formation histories of the thin and thick disks. Our results provide new clues for theoretical works on binary formation., Comment: 20 pages, 12 figures, ApJ accepted