arXiv subjects

Haining Li

Publications and source records attributed to Haining Li.

At least 37 records · Page 2Linked to original sources

arXiv2025

An Actinide-boost Star Discovered in the Gaia-Sausage-Enceladus

We report the discovery of an actinide-boost, very metal-poor ($\left[\mathrm{Fe/H} \right]=-2.38$), $r$-process-enhanced ($\left[\mathrm{Eu/Fe} \right]=0.80$) star, LAMOST J0804+5740, within the Gaia-Sausage-Enceladus (GSE). Based on the high-resolution ($R\sim36,000\; and \;60,000$) and high signal-to-noise ratio spectra obtained with the High Dispersion Spectrograph on the Subaru Telescope, the abundances of 48 species are determined. Its $\logε\rm(\mathrm{Th}/\mathrm{Eu}) = -0.22 $ establishes it as the first confirmed actinide-boost star within the GSE. Comparative analysis of its abundance pattern with theoretical $r$-process models reveals that the magnetorotationally driven jet supernova $r$-process model with $\hat{L}v$ = 0.2 provides the best fit and successfully reproduces the actinide-boost signature. Kinematic analysis of actinide-boost stars reveals that approximately two-thirds of them are classified as $\textit{ex-situ}$ stars, suggesting that actinide-boost stars are more likely to originate from accreted dwarf galaxies. As the first actinide-boost star identified within the GSE, J0804+5740 will provide valuable insights into $r$-process nucleosynthesis in accreted dwarf galaxies like the GSE, especially on the production of the heaviest elements.

astro-ph.SR↗

arXiv2025

A Catalog of 12,766 Carbon-enhanced Metal-poor Stars from LAMOST Data Release 8

Metal-poor stars are a rare and ancient type of stars; Carbon-Enhanced Metal-Poor (CEMP) stars are a subset of these celestial bodies that show an enrichment of carbon relative to iron. They are believed to be formed from gas polluted by the first generation of stars after the Big Bang and are important objects for studying the early universe, galaxy evolution, and nucleosynthesis. Due to their rarity, the search for metal-poor stars and CEMP stars is a valuable task. This study investigates the search for CEMP stars based on the low-resolution stellar spectra from LAMOST DR8, and proposes a deep learning scheme. From the LAMOST DR8 spectral library, this work discovered 12,766 CEMP star candidates. For ease of reference and use, we provide the estimated parameters $T_\texttt{eff}$, $\log~g$, [Fe/H] and [C/H] for them.

astro-ph.SR↗

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

astro-ph.SR↗

arXiv2024

Planets Around Solar Twins/Analogs (PASTA) I.: High precision stellar chemical abundance for 17 planet-hosting stars and the condensation temperature trend

The Sun is depleted in refractory elements compared to nearby solar twins, which may be linked to the formation of giant or terrestrial planets. Here we present high-resolution, high signal-to-noise spectroscopic data for 17 solar-like stars hosting planets, obtained with Magellan II/MIKE, to investigate whether this depletion is related to planet formation. We derive stellar parameters, including stellar atmosphere, age, radius, mass, and chemical abundances for 22 elements from carbon to europium through line-by-line differential analysis. Our uncertainties range from 0.01 dex for Fe and Si to 0.08 dex for Sr, Y, and Eu. By comparing the solar abundances to those of the 17 stars, we investigate the differential abundance ([X/Fe]$_{\rm solar}$ - [X/Fe]$_{\rm star}$) versus condensation temperature ($T_c$) trend. In particular, we apply Galactic chemical evolution corrections to five solar twins within the full sample. Our results conform to previous studies that the Sun is relatively depleted in refractory compared to volatile elements. For both five solar twins and the rest of solar-like stars, we find that all stars hosting known gas giant planets exhibit negative $T_c$ trend slopes, suggesting that the Sun is relatively depleted in refractory elements compared to similar giant-planet-host stars. Additionally, we find no correlation between $T_c$ trend slopes and the total mass of detected terrestrial planets in each system, suggesting that terrestrial planet formation may not be the cause of refractory element depletion in the Sun.

astro-ph.SR↗

arXiv2024

The Stellar Abundances and Galactic Evolution Survey (SAGES) III -- The g/r/i-band Data Release

The Stellar Abundances and Galactic Evolution Survey (SAGES) is a multi-band survey that covers the northern sky area of ~12000 deg2. Nanshan One-meter Wide-field Telescope (NOWT) of Xinjiang Astronomical Observatory (XAO) carried out observations on g/r/i bands. We present here the survey strategy, data processing, catalog construction, and database schema. The observations of NOWT started in 2016 August and was completed in 2018 January, total 17827 frames were obtained and ~4600 deg2 sky areas were covered. In this paper, we released the catalog of the data in the g/r/i bands observed with NOWT. In total, there are 109,197,578 items of the source records. The catalog is the supplement for the SDSS for the bright end, and the combination of our catalog and these catalogs could be helpful for source selections for other surveys and the Milky Way sciences, e.g., white dwarf candidates and stellar flares.

astro-ph.GA↗

arXiv2024

A Modified Initial Mass Function of the First Stars with Explodability Theory under Different Enrichment Scenarios

The most metal-poor stars record the earliest metal enrichment triggered by Population III stars. By comparing observed abundance patterns with theoretical yields of metal-free stars, physical properties of their first star progenitors can be inferred, including zero-age main-sequence mass and explosion energy. In this work, the initial mass distribution (IMF) of first stars is obtained from the largest analysis to date of 406 very metal-poor stars with the newest LAMOST/Subaru high-resolution spectroscopic observations. However, the mass distribution fails to be consistent with the Salpeter IMF, which is also reported by previous studies. Here we modify the standard power-law function with explodability theory. The mass distribution of Population III stars could be well explained by ensuring the initial metal enrichment to originate from successful supernova explosions. Based on the modified power-law function, we suggest an extremely top-heavy or nearly flat initial mass function with a large explosion energy exponent. This indicates that supernova explodability should be considered in the earliest metal enrichment process in the Universe.

astro-ph.GA↗

arXiv2024

Four-hundred Very Metal-poor Stars Studied with LAMOST and Subaru. III. Dynamically Tagged Groups and Chemodynamical Properties

Very metal-poor (VMP) stars record the signatures of early accreted galaxies, making them essential tools for unraveling the early stages of Galaxy formation. Understanding the origin of VMP stars requires comprehensive studies of their chemical compositions and kinematics, which are currently lacking. Hence, we conduct a chemodynamical analysis of 352 VMP stars selected from one of the largest uniform high-resolution VMP star samples, jointly obtained from LAMOST and Subaru. We apply a friends-of-friends clustering algorithm to the master catalog of this high-resolution sample, which consists of 5778 VMP stars. It results in 131 dynamically tagged groups with 89 associated with known substructures in the Milky Way, including Gaia-Sausage-Enceladus (GSE), Thamnos, Helmi streams, Sequoia, Wukong, Pontus, and the very metal-poor disk (VMPD). Our findings are: (i) the VMPD shows lower Zn abundances than the rest, which indicates that it could be a relic of small stellar systems; (ii) Sequoia shows moderately high r-process abundances; (iii) Helmi streams show deficiencies in carbon and light neutron-capture elements; (iv) the fraction of carbon-enhanced metal-poor stars with no enhancement in heavy elements (CEMP-no stars) seems low in the VMPD and the Helmi streams; and (v) a subgroup in GSE exhibits a very high fraction of r-process enhanced stars, with four out of five showing [Eu/Fe]> +1.0. The abundance patterns of other elements in VMP substructures largely match the whole VMP sample. We also study large-scale correlations between abundance ratios and kinematics without classifying stars into substructures, but it does not yield significant correlations once the overall chemical evolution is considered for most elements.

astro-ph.GA↗

arXiv2024

The Kinematic and Chemical Properties of the Close-in Planet Host Star 8 UMi

A recent study by Hon et al. reported that a close-in planet around the red clump star, 8 UMi, should have been engulfed during the expansion phase of its parent star's evolution. They explained the survival of this exoplanet through a binary-merger channel for 8 UMi. The key to testing this formation scenario is to derive the true age of this star: is it an old "imposter" resulting from a binary merger, or a genuinely young red clump giant? To accomplish this, we derive kinematic and chemical properties for 8 UMi using astrometric data from {\it Gaia} DR3 and the element-abundance pattern measured from a high-resolution ($R \sim 75,000$) spectrum taken by SOPHIE. Our analysis shows that 8 UMi is a normal thin-disk star with orbital rotation speed of $\it{V}_\mathrmϕ=\mathrm{244.96 km s^{-1}}$, and possesses a Solar metallicity ([Fe/H] $= -0.05 \pm 0.07$) and $α$-element abundance ratio ([$α$/Fe] $= +0.01 \pm 0.03$). By adopting well-established relationships between age and space velocities/elemental abundances, we estimate a kinematic age of $3.50^{+3.00}_{-2.00}$ Gyr, and a chemical age of $3.25^{+2.50}_{-1.50}$ Gyr from [C/N] and $3.47 \pm 1.96$ Gyr from [Y/Mg] for 8 UMi, respectively. These estimates are consistent with the isochrone-fitting age ($1.90^{+1.15}_{-0.30}$ Gyr) of 8 UMi, but are all much younger than the timescale required in a binary-merger scenario. This result challenges the binary-merger model; the existence of such a closely orbiting exoplanet around a giant star remains a mystery yet to be resolved.

astro-ph.EP↗

arXiv2024

Determining Stellar Elemental Abundances from DESI Spectra with the Data-Driven Payne

Stellar abundances for a large number of stars are key information for the study of Galactic formation history. Large spectroscopic surveys such as DESI and LAMOST take median-to-low resolution ($R\lesssim5000$) spectra in the full optical wavelength range for millions of stars. However, line blending effect in these spectra causes great challenges for the elemental abundances determination. Here we employ the DD-PAYNE, a data-driven method regularised by differential spectra from stellar physical models, to the DESI EDR spectra for stellar abundance determination. Our implementation delivers 15 labels, including effective temperature $T_{\rm eff}$, surface gravity $\log g$, microturbulence velocity $v_{\rm mic}$, and abundances for 12 individual elements, namely C, N, O, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, Ni. Given a spectral signal-to-noise ratio of 100 per pixel, internal precision of the label estimates are about 20 K for $T_{\rm eff}$, 0.05 dex for $\log~g$, and 0.05 dex for most elemental abundances. These results are agree with theoretical limits from the Crámer-Rao bound calculation within a factor of two. The Gaia-Enceladus-Sausage that contributes the majority of the accreted halo stars are discernible from the disk and in-situ halo populations in the resultant [Mg/Fe]-[Fe/H] and [Al/Fe]-[Fe/H] abundance spaces. We also provide distance and orbital parameters for the sample stars, which spread a distance out to $\sim$100 kpc. The DESI sample has a significant higher fraction of distant (or metal-poor) stars than other existed spectroscopic surveys, making it a powerful data set to study the Galactic outskirts. The catalog is publicly available.

astro-ph.GA↗

arXiv2024

Spectacular nucleosynthesis from early massive stars

Stars formed with initial mass over 50 Msun are very rare today, but they are thought to be more common in the early universe. The fates of those early, metal-poor, massive stars are highly uncertain. Most are expected to directly collapse to black holes, while some may explode as a result of rotationally powered engines or the pair-creation instability. We present the chemical abundances of J0931+0038, a nearby low-mass star identified in early followup of SDSS-V Milky Way Mapper, which preserves the signature of unusual nucleosynthesis from a massive star in the early universe. J0931+0038 has relatively high metallicity ([Fe/H] = -1.76 +/- 0.13) but an extreme odd-even abundance pattern, with some of the lowest known abundance ratios of [N/Fe], [Na/Fe], [K/Fe], [Sc/Fe], and [Ba/Fe]. The implication is that a majority of its metals originated in a single extremely metal-poor nucleosynthetic source. An extensive search through nucleosynthesis predictions finds a clear preference for progenitors with initial mass > 50 Msun, making J0931+0038 one of the first observational constraints on nucleosynthesis in this mass range. However the full abundance pattern is not matched by any models in the literature. J0931+0038 thus presents a challenge for the next generation of nucleosynthesis models and motivates study of high-mass progenitor stars impacted by convection, rotation, jets, and/or binary companions. Though rare, more examples of unusual early nucleosynthesis in metal-poor stars should be found in upcoming large spectroscopic surveys.

astro-ph.SR↗

arXiv2023

Unique chemical composition of the very metal-poor star LAMOST J1645+4357

We report on the chemical composition of the very metal-poor ([Fe/H]=-2.9) star LAMOST J1645+4357 that is identified to be a red giant having peculiar abundance ratios by Li et al. (2022). The standard abundance analysis is carried out for this object and the well studied metal-poor star HD~122563 that has similar atmospheric parameters. LAMOST J1645+4357 has a remarkable abundance set, highlighted by these features: (1) Nitrogen is significantly enhanced ([N/Fe]=+1.4) and the total abundance of C and N is also very high ([(C+N)/Fe]=+0.9); (2) alpha-elements are over-abundant with respect to iron as generally found in very metal-poor stars; (3) Ti, Sc, Co and Zn are significantly deficient; (4) Cr and Mn are enhanced compared to most of very metal-poor stars; (5) Sr and Ba are deficient and the Sr/Ba ratio ([Sr/Ba]=-1.0) is significantly lower than the value expected for the r-process. The overall abundance pattern of this object from C to Zn is well reproduced by a faint supernova model assuming spherical explosion, except for the excess of Cr and Mn which requires enhancement of incomplete Si burning or small contributions of a type Ia supernova or a pair-instability supernova. There remains, however, a question why the abundance pattern of this star is so unique among very metal-poor stars.

astro-ph.SR↗

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.

astro-ph.GA↗

arXiv2022

Stellar Loci VI: An Updated Catalog of the Best and Brightest Metal-poor Stars

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.

astro-ph.SR↗

arXiv2022

Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20$\leq$SNR$<$30

The accuracy of the estimated stellar atmospheric parameter decreases evidently with the decreasing of spectral signal-to-noise ratio (SNR) and there are a huge amount of this kind observations, especially in case of SNR$<$30. Therefore, it is helpful to improve the parameter estimation performance for these spectra and this work studied the ($T_\texttt{eff}, \log~g$, [Fe/H]) estimation problem for LAMOST DR8 low-resolution spectra with 20$\leq$SNR$<$30. We proposed a data-driven method based on machine learning techniques. Firstly, this scheme detected stellar atmospheric parameter-sensitive features from spectra by the Least Absolute Shrinkage and Selection Operator (LASSO), rejected ineffective data components and irrelevant data. Secondly, a Multi-layer Perceptron (MLP) method was used to estimate stellar atmospheric parameters from the LASSO features. Finally, the performance of the LASSO-MLP was evaluated by computing and analyzing the consistency between its estimation and the reference from the APOGEE (Apache Point Observatory Galactic Evolution Experiment) high-resolution spectra. Experiments show that the Mean Absolute Errors (MAE) of $T_\texttt{eff}, \log~g$, [Fe/H] are reduced from the LASP (137.6 K, 0.195 dex, 0.091 dex) to LASSO-MLP (84.32 K, 0.137 dex, 0.063 dex), which indicate evident improvements on stellar atmospheric parameter estimation. In addition, this work estimated the stellar atmospheric parameters for 1,162,760 low-resolution spectra with 20$\leq$SNR$<$30 from LAMOST DR8 using LASSO-MLP, and released the estimation catalog, learned model, experimental code, trained model, training data and test data for scientific exploration and algorithm study.

astro-ph.GA↗

arXiv2022

Overview of the LAMOST survey in the first decade

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.

astro-ph.GA↗

arXiv2022

Trustworthy Long-Tailed Classification

Classification on long-tailed distributed data is a challenging problem, which suffers from serious class-imbalance and accordingly unpromising performance especially on tail classes. Recently, the ensembling based methods achieve the state-of-the-art performance and show great potential. However, there are two limitations for current methods. First, their predictions are not trustworthy for failure-sensitive applications. This is especially harmful for the tail classes where the wrong predictions is basically frequent. Second, they assign unified numbers of experts to all samples, which is redundant for easy samples with excessive computational cost. To address these issues, we propose a Trustworthy Long-tailed Classification (TLC) method to jointly conduct classification and uncertainty estimation to identify hard samples in a multi-expert framework. Our TLC obtains the evidence-based uncertainty (EvU) and evidence for each expert, and then combines these uncertainties and evidences under the Dempster-Shafer Evidence Theory (DST). Moreover, we propose a dynamic expert engagement to reduce the number of engaged experts for easy samples and achieve efficiency while maintaining promising performances. Finally, we conduct comprehensive experiments on the tasks of classification, tail detection, OOD detection and failure prediction. The experimental results show that the proposed TLC outperforms existing methods and is trustworthy with reliable uncertainty.

cs.LG↗

arXiv2022

Four-hundred Very Metal-Poor Stars Studied with LAMOST and Subaru. II. Elemental abundances

We present homogeneous abundance analysis of over 20 elements for 385 very metal-poor (VMP) stars based on the LAMOST survey and follow-up observations with the Subaru Telescope. It is the largest high-resolution VMP sample (including 363 new objects) studied by a single program, and the first attempt to accurately determine evolutionary stages for such a large sample based on Gaia parallaxes. The sample covers a wide metallicity range from [Fe/H]=-1.7 down to [Fe/H]=-4.3, including over 110 objects with [Fe/H]<-3.0. The expanded coverage in evolutionary status makes it possible to define abundance trends respectively for giants and turn-off stars. The newly obtained abundance data confirm most abundance trends found by previous studies, but also provide useful update and new sample of outliers. The Li plateau is seen in -2.5 < [Fe/H] <-1.7 in our sample, whereas the average Li abundance is clearly lower at lower metallicity. Mg, Si, and Ca are overabundant with respect to Fe, showing decreasing trend with increasing metallicity. Comparisons with chemical evolution models indicate that the over-abundance of Ti, Sc, and Co are not well reproduced by current theoretical predictions. Correlations are seen between Sc and alpha-elements, while Zn shows a detectable correlation only with Ti but not with other alpha-elements. The fraction of carbon-enhanced stars ([C/Fe]> 0.7) is in the range of 20-30% for turn-off stars depending on the treatment of objects for which C abundance is not determined, which is much higher than that in giants (~8%). Twelve Mg-poor stars ([Mg/Fe] < 0.0) have been identified in a wide metallicity range from [Fe/H] =-3.8 through -1.7. Twelve Eu-rich stars ([Eu/Fe]> 1.0) have been discovered in -3.4 <[Fe/H]< -2.0, enlarging the sample of r-process-enhanced stars with relatively high metallicity.

astro-ph.SR↗

arXiv2022

Four-hundred Very Metal-poor Stars studied with LAMOST and Subaru. I. Survey Design, Follow-up Program, and Binary Frequency

The chemical abundances of very metal-poor stars provide important constraints on the nucleosynthesis of the first generation of stars and early chemical evolution of the Galaxy. We have obtained high-resolution spectra with the Subaru Telescope for candidates of very metal-poor stars selected with a large survey of Galactic stars carried out with LAMOST. In this series of papers, we report on the elemental abundances of about 400 very metal-poor stars and discuss the kinematics of the sample obtained by combining the radial velocities measured in this study and recent astrometry obtained with Gaia. This paper provides an overview of our survey and follow-up program, and reports radial velocities for the whole sample. We identify seven double-lined spectroscopic binaries from our high-resolution spectra, for which radial velocities of the components are reported. We discuss the frequency of such relatively short-period binaries at very low metallicity.

astro-ph.SR↗