Low-resolution Stellar Spectra Research Articles

Very metal-poor stars I: a catalogue derived from LAMOST DR9

ABSTRACT In this paper, a semisupervised machining learning technique had been utilized to analyse low-resolution stellar spectra from Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) Data Release 9 (DR9). We identified approximately 111 000 potential very metal-poor stars. Estimation of their stellar parameters ($T_{\rm eff}$, ${\rm log}\, \rm {g}$, [Fe/H]) indicate that over 99 per cent are metal-poor ([Fe/H] < −1.0), comprising 32 631 very metal-poor ([Fe/H] < −2.0), 702 extremely metal-poor ([Fe/H] < −3.0) and 30 ultra metal-poor ([Fe/H] < −4.0) stars. Based on kinematic characteristics, stars were categorized into thick disc-like, thin disc-like, and halo-like groups. We analysed their metallicity distributions (MDs) with respect to vertical height ($|Z|$) and orbital eccentricity (e). Thick disc-like stars in current sample show a clear trend of decreasing metallicty with increasing $|Z|$ or e for the ranges −3.0 $\lt $ [Fe/H] $\lt $ −1.2 and $|Z|$$\lt $ 3 kpc. Conversely, thin disc-like stars in current sample exhibit a slight increase in the fraction of more metal-poor stars with $|Z|$ for the ranges −3.0 $\lt $ [Fe/H] $\lt $ −1.2 and $|Z|$$\lt$ 1 kpc, but no obvious correlation with e. Additionally, we confirmed the presence of two prominent substructures among halo-like stars. One exhibits a high eccentricity ($e\ \gt\ 0.8$) orbit and higher metallicity, while the other follows a retrograde orbit with moderate eccentricity ($e\sim 0.6$) and lower metallicity. We believe they are related to the merger events known as Gaia Sausage and Sequoia, respectively. Furthermore, our observations indicate that the Sequoia has lower eccentricity and metallicity compared to the Gaia Sausage.

Estimating atmospheric parameters from LAMOST low-resolution spectra with low SNR

ABSTRACT Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) acquired tens of millions of low-resolution stellar spectra. The large amount of the spectra result in the urgency to explore automatic atmospheric parameter estimation methods. There are lots of LAMOST spectra with low signal-to-noise ratios (SNR), which result in a sharp degradation on the accuracy of their estimations. Therefore, it is necessary to explore better estimation methods for low-SNR spectra. This paper proposed a neural network-based scheme to deliver atmospheric parameters, LASSO-MLPNet. Firstly, we adopt a polynomial fitting method to obtain pseudo-continuum and remove it. Then, some parameter-sensitive features in the existence of high noises were detected using Least Absolute Shrinkage and Selection Operator (LASSO). Finally, LASSO-MLPNet used a Multilayer Perceptron network (MLPNet) to estimate atmospheric parameters Teff, log g, and [Fe/H]. The effectiveness of the LASSO-MLPNet was evaluated on some LAMOST stellar spectra of the common star between the Apache Point Observatory Galactic Evolution Experiment (APOGEE) and LAMOST. It is shown that the estimation accuracy is significantly improved on the stellar spectra with 10 < SNR ≤ 80. Especially, LASSO-MLPNet reduces the mean absolute error (MAE) of the estimation of Teff, log g, and [Fe/H] from [144.59 K, 0.236 dex, 0.108 dex; LAMOST Stellar Parameter Pipeline (LASP)] to (90.29 K, 0.152 dex, 0.064 dex; LASSO-MLPNet) on the stellar spectra with 10 < SNR ≤ 20. To facilitate reference, we release the estimates of the LASSO-MLPNet from more than 4.82 million stellar spectra with 10 < SNR ≤ 80 and 3500 < SNRg ≤ 6500 as a value-added output.

Objective Separation between CP1 and CP2 Based on Feature Extraction with Machine Learning

In the eighth data release (DR8) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, more than 318,740 low-resolution stellar spectra with types from B to early F and signal-to-noise ratios >50 were released. With this large volume of the early-type stars, we tried machine-learning algorithms to search for class-one and class-two chemical peculiars (CP1 and CP2), and to detect spectral features to distinguish the two classes in low-resolution spectra. We selected the XGBoost algorithm after comparing the classification efficiency of three machine-learning ensemble algorithms. Using XGBoost followed by the visual investigation, we presented a catalog of 20,694 sources, including 17,986 CP1 and 2708 CP2, in which 6917 CP1 and 1652 CP2 are newly discovered. We also list the spectral features to separate CP1 from CP2 discovered through XGBoost. The stellar parameters (including effective temperature (T eff), surface gravity (log g), metallicity [Fe/H]), the spatial distribution in Galactic coordinates, and the color magnitude were provided for all of the entries of the catalog. The T eff for CP1 distributes from ∼6000 to ∼8500 K, while for CP2 it distributes from ∼7000 to ∼13,700 K. The log g of CP1 ranges from 2.8 to 4.8 dex, peaking at 4.5 dex, and of CP2 it ranges from 2.0 to 5.0 dex, peaking at 3.6 dex, respectively. The [Fe/H] of CP1 and CP2 are from −1.4 to 0.4 dex, and the [Fe/H] of CP1 are on average higher than that of CP2. Almost all of the targets in our sample locate around the Galactic plane.

Determination of Sodium Abundance Ratio from Low-resolution Stellar Spectra and Its Applications

Abstract We present a method to determine sodium abundance ratios ([Na/Fe]) using the Na i D doublet lines in low-resolution (R ∼ 2000) stellar spectra. As stellar Na i D lines are blended with those produced by the interstellar medium, we developed a technique for removing the interstellar Na i D lines using the relationship between extinction, which is proportional to E(B − V), and the equivalent width of the interstellar Na i D absorption lines. When measuring [Na/Fe], we also considered corrections for nonlocal thermodynamic equilibrium (NLTE) effects. Comparisons with data from high-resolution spectroscopic surveys suggest that the expected precision of [Na/Fe] from low-resolution spectra is better than 0.3 dex for stars with [Fe/H] > −3.0. We also present a simple application employing the estimated [Na/Fe] values for a large number of stellar spectra from the Sloan Digital Sky Survey (SDSS). After classifying the SDSS stars into Na-normal, Na-high, and Na-extreme, we explore their relation to stars in Galactic globular clusters (GCs). We find that while the Na-high SDSS stars exhibit a similar metallicity distribution function (MDF) to that of the GCs, indicating that the majority of such stars may have originated from GC debris, the MDF of the Na-normal SDSS stars follows that of typical disk and halo stars. As there is a high fraction of carbon-enhanced metal-poor stars among the Na-extreme stars, they may have a non-GC origin, perhaps due to mass-transfer events from evolved binary companions.

Compact object candidates with K/M-dwarf companions from LAMOST low-resolution survey

Searching for compact objects (black holes, neutron stars, or white dwarfs) in the Milky Way is essential for understanding the stellar evolution history, the physics of compact objects, and the structure of our Galaxy. Compact objects in binaries with a luminous stellar companion are perfect targets for optical observations. Candidate compact objects can be achieved by monitoring the radial velocities of the companion star. However, most of the spectroscopic telescopes usually obtain stellar spectra at a relatively low efficiency, which makes a sky survey for millions of stars practically impossible. The efficiency of a large-scale spectroscopic survey, the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST), presents a specific opportunity to search for compact object candidates, i.e., simply from the spectroscopic observations. Late-type K/M stars are the most abundant populations in our Galaxy. Owing to the relatively large Keplerian velocities in the close binaries with a K/M-dwarf companion, a hidden compact object could be discovered and followed-up more easily. In this study, compact object candidates with K/M-dwarf companions are investigated with the LAMOST low-resolution stellar spectra. Based on the LAMOST Data Release 5, we obtained a sample of $56$ binaries, each containing a K/M-dwarf with a large radial velocity variation $\Delta V_{\rm R} > 150~{\rm km~s}^{-1}$. Complemented with the photometric information from the Transiting Exoplanet Survey Satellite, we derived a sample of $35$ compact object candidates, among which, the orbital periods of $16$ sources were revealed by the light curves. Considering two sources as examples, we confirmed that a compact object existed in the two systems by fitting the radial velocity curve. This study demonstrates the principle and the power of searching for compact objects through LAMOST.

The Stars of the HETDEX Survey. I. Radial Velocities and Metal-poor Stars from Low-resolution Stellar Spectra

Abstract The Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) is an unbiased, massively multiplexed spectroscopic survey, designed to measure the expansion history of the universe through low-resolution (R ∼ 750) spectra of Lyα emitters. In its search for these galaxies, HETDEX will also observe a few times 105 stars. In this paper, we present the first stellar value-added catalog within the internal second data release of the HETDEX Survey (HDR2). The new catalog contains 120,571 low-resolution spectra for 98,736 unique stars between 10 < G < 22 spread across the HETDEX footprint at relatively high (b ∼ 60°) Galactic latitudes. With these spectra, we measure radial velocities (RVs) for ∼42,000 unique FGK-type stars in the catalog and show that the HETDEX spectra are sufficient to constrain these RVs with a 1σ precision of 28.0 km s−1 and bias of 3.5 km s−1 with respect to the Large Sky Area Multi-Object Fibre Spectroscopic Telescope surveys and 1σ precision of 27.5 km s−1 and bias of 14.0 km s−1 compared to the Sloan Extension for Galactic Understanding and Exploration survey. Since these RVs are for faint (G ≥ 16) stars, they will be complementary to Gaia. Using t-Distributed Stochastic Neighbor Embedding (tSNE), we also demonstrate that the HETDEX spectra can be used to determine a star’s T eff, and log g and its [Fe/H]. With the tSNE projection of the FGK-type stars with HETDEX spectra we also identify 416 new candidate metal-poor ([Fe/H] < −1 dex) stars for future study. These encouraging results illustrate the utility of future low-resolution stellar spectroscopic surveys.

A Method of Estimating the [α/Fe] Ratios from Low-resolution Stellar Spectratwo

A method for the determination of [α/Fe] from low-resolution stellar spectra is presented. The proposed scheme includes the following three steps: firstly, the spectrum is decomposed by the multi-scale Haar wavelet, and the high-frequency components are removed to suppress the high-frequency noise; then, based on the correlation of the spectral data component with [α/Fe], the spectral features are selected by the LASSO (Least Absolute Shrinkage and Selection Operator) algorithm; finally, [α/Fe] is measured by the multiple linear regression method based on the MARCS stellar spectrum library. The effectiveness of the method is verified with the low-resolution stellar spectra of ELODIE, SDSS (Sloan Digital Sky Survey), LAMOST (Large Sky Area Multi-Object Fibre Spectroscopic Telescope), and four star clusters. The systematic deviations and accuracies are as follows: (0.04dex, 0.064dex) for the 317 ELODIE spectra; (0.16dex, 0.065dex) for the 412 SDSS spectra; (0.05dex, 0.062dex) for the 1276 LAMOST spectra (with the signal-noise ratio in the g band (SNRG) greater than 20). The averages of [α/Fe] obtained for the likely members of the globular star clusters (M13, M15) and open star clusters (NGC2420, M67) are in agreement with the literature values.

Prospects for Measuring Abundances of >20 Elements with Low-resolution Stellar Spectra

Abstract Understanding the evolution of the Milky Way calls for the precise abundance determination of many elements in many stars. A common perception is that deriving more than a few elemental abundances ([Fe/H], [α/Fe], perhaps [C/H], [N/H]) requires medium-to-high spectral resolution, R ≳ 10,000, mostly to overcome the effects of line blending. In a recent work, we presented an efficient and practical way to model the full stellar spectrum, even when fitting a large number of stellar labels simultaneously. In this paper, we quantify to what precision the abundances of many different elements can be recovered, as a function of spectroscopic resolution and wavelength range. In the limit of perfect spectral models and spectral normalization, we show that the precision of elemental abundances is nearly independent of resolution, for a fixed exposure time and number of detector pixels; low-resolution spectra simply afford much higher S/N per pixel and generally larger wavelength range in a single setting. We also show that estimates of most stellar labels are not strongly correlated with one another once R ≳ 1000. Modest errors in the line-spread function, as well as small radial velocity errors, do not affect these conclusions, and data-driven models indicate that spectral (continuum) normalization can be achieved well enough in practice. These results, to be confirmed with an analysis of observed low-resolution data, open up new possibilities for the design of large spectroscopic stellar surveys and for the reanalysis of archival low-resolution data sets.

New Low-mass Stars in the 25 Orionis Stellar Group and Orion OB1a Sub-association from SDSS-III/BOSS Spectroscopy

Abstract The Orion OB1a sub-association is a rich low-mass star (LMS) region. Previous spectroscopic studies have confirmed 160 LMSs in the 25 Orionis stellar group (25 Ori), which is the most prominent overdensity of Orion OB1a. Nonetheless, the current census of the 25 Ori members is estimated to be lower than 50% complete, leaving a large number of members to be still confirmed. We retrieved 172 low-resolution stellar spectra in Orion OB1a observed as ancillary science in the SDSS-III/BOSS survey, for which we classified their spectral types and determined physical parameters. To determine memberships, we analyzed the emission, Li i λ6708 absorption, and Na i λλ8183, 8195 absorption as youth indicators in stars classified as M type. We report 50 new LMSs spread across the 25 Orionis, ASCC 18, and ASCC 20 stellar groups with spectral types from M0 to M6, corresponding to a mass range of . This represents an increase of 50% in the number of known LMSs in the area and a net increase of 20% in the number of 25 Ori members in this mass range. Using parallax values from the Gaia DR1 catalog, we estimated the distances to these three stellar groups and found that they are all co-distant, at 338 ± 66 pc. We analyzed the spectral energy distributions of these LMSs and classified their disks into evolutionary classes. Using H-R diagrams, we found a suggestion that 25 Ori could be slightly older than the other two observed groups in Orion OB1a.

NEWLY DISCOVERED ALPHA-POOR STARS IN THE SOLAR NEIGHBORHOOD

We present an abundance analysis for two newly discovered α-poor stars based on high-resolution spectroscopy. These stars were previously identified in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 1 as candidate α-poor stars. We observed these candidate α-poor stars with the Magellan Inamori Kyocera Echelle (MIKE) spectrograph on the 6.5 m Magellan-Clay Telescope located at Las Campanas Observatory. This high-resolution analysis confirms the low [α/Fe] abundance ratios for these stars compared to those of the majority of Galactic stars with comparable metallicities ([Fe/H] ∼ ). The large deficiencies of α-elements suggest that these stars possess an anomalous chemical enrichment history. To have found such α-poor stars in our sample indicates that large scatters of the α-element abundance ratios may exist near solar metallicity. These results also demonstrate that our method is capable of selecting α-poor stars from low-resolution stellar spectra.

Searching for extremely alpha-poor stars in the Galactic Halo

AbstractA few alpha-poor stars that show severe departures (over 0.4 dex deficiency in alpha-element abundance) from the general enhanced alpha-element chemical abundance trends of the halo have been discovered in recent years, such as BD +80°245, G4-36 and CS 22966-043. These ratios suggest a different chemical enrichment history for these stars than for the majority of the halo. Similarly low-alpha abundance patterns are also seen in the Sagittarius dSph galaxy. We present a method for searching of extremely alpha-poor stars from low-resolution stellar spectra of LAMOST pilot survey and attempt to create a large sample of these particular Galactic halo stars.

The mean stellar parameters from IUE and hipparcos data

We elaborate an automatic procedure fitting theoretical flux distributions (Kurucz 1996) to observed low resolution stellar spectra. The procedure is based on the least squares optimalization algorithm and enable us to determine the basic stellar parameters, which minimize RMS (Root Mean Square). This efficient method allows us to retrieve simultaneously T eff , log g, [m/H], θ and E(B–V). To check how reduction procedure can influence the results, we use observations reduced by both NEWSIPS and INES packages. We also calibrate our procedure by an analysis of the standard stars studied by Code et al. (1976). Using the IUE/NEWSIPS observations we find stellar parameters slightly overestimated in comparison with the fundamental data given by Code et al., viz., Δ log T eff =0.002, Δθ=0.03, Δ log L/ L ⊙=0.12 and Δ log R/ R ⊙=0.05. We also apply our method for stars located in Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC). We find satisfactory solutions for [m/H] for these metal deficient objects, viz., on average −1.2 dex and −0.6 dex for SMC and LMC stars, respectively. The results presented in this paper indicate that the low dispersion spectra collected by means of small satellites can be used to determine the fundamental stellar parameters even for extragalactic stars.