arXiv subjects

Yihan Song

Publications and source records attributed to Yihan Song.

8 recordsLinked to original sources

arXiv2026

The Stellar Abundances and Galactic Evolution Survey (SAGES). V. The First Data Release of the DDO51 Band

We present the first public data release of DDO51 band from the Stellar Abundances and Galactic Evolution Survey (SAGES), based on Nanshan One-meter Wide-field Telescope (NOWT) observations obtained between 2023 September and 2024 January. This release initiates the DDO51-band component of the survey, covering $\sim$ 2,500 deg$^2$ of the northern sky and including more than 10 million sources. The DDO51 filter is centered near the \ion{Mg}{1}~$b$ triplet and the adjacent MgH feature, offering sensitivity to stellar surface gravity. The data reduction pipeline incorporates an improved astrometric solution anchored to Gaia DR3 and a photometric calibration strategy tied to synthetic photometry from Gaia XP spectra. These procedures yield a point-source depth of $\sim$18.9 mag at S/N$\sim$10 and an internal photometric precision $\approx$6-7 mmag at the bright end. A preliminary color--color analysis using Gaia broadband photometry confirms the expected sensitivity of the DDO51 band to stellar surface gravity, demonstrating a clear photometric separation between dwarf and giant sequences for late-type stars. This dataset, when combined with existing SAGES photometry in other bands, provides a crucial tool for disentangling the substructures of the Milky Way. All data products from this release upon publication will be available.

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arXiv2026

The Spectroscopic and Photometric Study of a Star Cluster Sample in Andromeda Halo

Halo star clusters serve as vital tracers for the formation and evolution of the Andromeda galaxy. In this work, we present physical parameters for 29 M31 halo star clusters, derived from a combination of spectroscopic and photometric data. Low-resolution spectra were acquired using the BFOSC spectrograph on the NAOC Xinglong 2.16-m telescope. For the photometric analysis, we utilized uSC and vSAGE bands from the SAGE survey, complemented by archival data from GALEX(NUV, FUV), PAN-STARRS(grizy) and the 2MASS(JHK). Ages and metallicities were determined via ULySS (Vazdekis et al. and pegase-hr) SSP model and the Bruzual & Charlot (2003) (BC03) stellar population synthesis models. The derived parameters show good agreement with literature values. Notably, for three of these clusters, this study represents the first combined photometric and spectroscopic analysis.

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arXiv2025

The Stellar Abundances and Galactic Evolution Survey (SAGES). IV. Surface Gravity Estimation and Giant-Dwarf Separation with the DDO51 Filter

Reliable estimation of stellar surface gravity (log $g$) for a large sample is crucial for evaluating stellar evolution models and understanding galactic structure; However, it is not easy to accomplish due to the difficulty in gathering a large spectroscopic data set. Photometric sky survey using a specific filter, on the other hand, can play a substantial role in the assessment of log $g$. The Stellar Abundances and Galactic Evolution Survey (SAGES) utilizes eight filters to provide accurate stellar parameters for $\sim10^{7}$ stars, with its DDO51 intermediate-band filter specifically designed for robust log $g$ determination. In this work, the observed SAGES $u_{\rm SC}$ and $v_{\rm SAGES}$ photometry, the synthetic photometry in $g$, $r$, $i$, and DDO51 bands derived from \textit{Gaia} XP spectra are employed to investigate the importance of the DDO51 filter in the determination of log $g$. We applied machine-learning-based extinction correction and employed XGBoost models, trained on stellar parameters from LAMOST, to predict log $g$ using photometric data. By comparing model predicted log $g$ with LAMOST values, we find that including DDO51 filter improve the accuracies of log $g$ estimates by 21.0\% (from 0.224\,dex to 0.177\,dex) overall, and by 26.5\% (from 0.302\,dex to 0.222\,dex ) for GK-type stars, as compared to those obtained without DDO51. The DDO51 filter is also validated to be particularly effective for metal-poor stars ([Fe/H]$<$-1.0), where it significantly mitigates systematic biases. Our findings highlight the diagnostic power of the SAGES DDO51 filter, providing enhanced stellar characterization vital for future in-depth studies of the Milky Way.

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arXiv2025

Looking for Signs of Unresolved Binarity in the Continuum of LAMOST Stellar Spectra

We describe an attempt to derive the binarity rate of samples of 166 A-, F-, G-, and K-type stars from LAMOST DR5 and 1000 randomly selected presumably single stars from Gaia DR3 catalogs. To this end, we compared continua of the observed spectra with the continua of synthetic spectra in the 3700 to 9097 Angstrom range. The latter spectra were reduced to the LAMOST set of wavelengths, while the former ones were smoothed. Next, we searched for every observed star the nearest synthetic spectrum using a four-parameter representation - effective temperature, gravity, [Fe/H], and a range of interstellar absorption values. However, rms deviations of observed spectra from synthetic ones appeared to be not sufficient to claim that any of the stars is a binary. We conclude that comparison of the intensity of pairs of spectral lines remains the best way to detect binarity.

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arXiv2025

The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning-Based Stellar parameters for 21 million stars from the First Data Release

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, and Teff, based on a combination of medium-band and broad-band photometric observations. Our analysis employs data primarily sourced from the SAGE Survey , which aims to observe much of the Northern Hemisphere. We combine the $uv$-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 for Teff. Furthermore, by incorporating 2MASS and WISE infrared photometric and GALEX 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 dataset for research on metal-poor stars, the structure of the Milky Way, and beyond. With the forthcoming release of additional bands from SAGE Survey such DDO51 and H-alpha, this versatile machine learning approach is poised to play an important role in upcoming surveys featuring expanded filter sets

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arXiv2023

The Stellar Abundances and Galactic Evolution Survey (SAGES) -- -- I. General Description and the First Data Release (DR1)

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.

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arXiv2015

A Large Sample of Am Candidates from LAMOST Data Release 1

We present a sample of metallic-line star (Am) candidates from the Large sky Area Multi-Object fiber Spectroscopic Telescope Data Release one (LAMOST DR1). According to the characteristic of under-abundance of calcium and overabundance of iron element of Am stars, we propose an empirical separation curve derived from line indices of Ca II K-line and iron lines we choose for low resolution spectra. 3537 Am candidates are ultimately selected from more than 30,000 stars which are classified as A-type or early-F stars by both LAMOST pipeline and visual inspection. Then we make some analysis on this sample and finally provide a list of these Am candidates with 10 relevant parameters. Comparing with other catalogues, Am candidates selected from LAMOST DR1 are much fainter on the whole. Obviously, our list is an important complementary to already known bright Am catalogues, and it offers valuable material for the research on this type of chemically peculiar stars.

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arXiv2013

White dwarf-main sequence binaries identified from the LAMOST pilot survey

We present a set of white dwarf-main sequence (WDMS) binaries identified spectroscopically from the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST, also called the Guo Shou Jing Telescope) pilot survey. We develop a color selection criteria based on what is so far the largest and most complete Sloan Digital Sky Survey (SDSS) DR7 WDMS binary catalog and identify 28 WDMS binaries within the LAMOST pilot survey. The primaries in our binary sample are mostly DA white dwarfs except for one DB white dwarf. We derive the stellar atmospheric parameters, masses, and radii for the two components of 10 of our binaries. We also provide cooling ages for the white dwarf primaries as well as the spectral types for the companion stars of these 10 WDMS binaries. These binaries tend to contain hot white dwarfs and early-type companions. Through cross-identification, we note that nine binaries in our sample have been published in the SDSS DR7 WDMS binary catalog. Nineteen spectroscopic WDMS binaries identified by the LAMOST pilot survey are new. Using the 3$σ$ radial velocity variation as a criterion, we find two post-common-envelope binary candidates from our WDMS binary sample.

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