Yi-Han Song

M DWARF CATALOG OF THE LAMOST PILOT SURVEY

We present a spectroscopic catalog of 58,360 M dwarfs from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope pilot survey. For each spectrum in the catalog, spectral subtype, radial velocity, Hα equivalent width, a number of prominent molecular band indices, and the metal-sensitive parameter ζ are provided. We use the Sloan Digital Sky Survey Data Release 7 Spectroscopic M dwarf catalog to verify the precision of our methods of classifying the spectral types and measuring the radial velocities. The magnetic activity properties of M dwarfs are also traced by Hα emission lines. The molecular band indices included in this catalog are sensitive to temperature or metallicity, and can be used for further study of the physical properties of M dwarfs. This M dwarf catalog is available on the Web site http://sciwiki.lamost.org/MCatalogPilot/.

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 3σ radial velocity variation as a criterion, we find two post-common-envelope binary candidates from our WDMS binary sample.

Relative flux calibration for the Guoshoujing Telescope (LAMOST)

This paper presents a relative flux calibration method for the Guoshoujing Telescope (LAMOST), which may be applied to connect a blue spectrum to a red spectrum to build the whole spectrum across the total wavelength range (3700 similar to 9000 angstrom). In each spectrograph, we estimate the effective temperatures of selected stars using a grid of spectral line indices in the blue spectral range and a comparison with stellar atmosphere models. For each spectrograph, stars of types A and F are selected as pseudo-standard stars, and the theoretical spectra are used to calibrate both the blue (3700 similar to 5900 angstrom) and red spectrograph arms (5700 similar to 9000 angstrom). Then the spectral response function for these pseudo-standard stars could be used to correct the raw spectra provided by the other fibers of the spectrograph, after a fiber efficiency function has been derived from twilight flat-field exposures. A key problem in this method is the fitting of a pseudo stellar continuum, so we also give a detailed description of this step. The method is tested by comparing a small sample of LAMOST spectra calibrated in this way on stars also observed by the Sloan Digital Sky Survey. The result shows that the T-eff estimation and relative flux calibration method are adequate.

LAMOST SPECTROGRAPH RESPONSE CURVES: STABILITY AND APPLICATION TO FLUX CALIBRATION

The task of flux calibration for Large sky Area Multi-Object Spectroscopic Telescope (LAMOST) spectra is difficult due to many factors, such as the lack of standard stars, flat-fielding for large field of view, and variation of reddening between different stars, especially at low Galactic latitudes. Poor selection, bad spectral quality, or extinction uncertainty of standard stars not only might induce errors to the calculated spectral response curve (SRC) but also might lead to failures in producing final 1D spectra. In this paper, we inspected spectra with Galactic latitude and reliable stellar parameters, determined through the LAMOST Stellar Parameter Pipeline (LASP), to study the stability of the spectrograph. To guarantee that the selected stars had been observed by each fiber, we selected 37,931 high-quality exposures of 29,000 stars from LAMOST DR2, and more than seven exposures for each fiber. We calculated the SRCs for each fiber for each exposure and calculated the statistics of SRCs for spectrographs with both the fiber variations and time variations. The result shows that the average response curve of each spectrograph (henceforth ASPSRC) is relatively stable, with statistical errors ≤10%. From the comparison between each ASPSRC and the SRCs for the same spectrograph obtained by the 2D pipeline, we find that the ASPSRCs are good enough to use for the calibration. The ASPSRCs have been applied to spectra that were abandoned by the LAMOST 2D pipeline due to the lack of standard stars, increasing the number of LAMOST spectra by 52,181 in DR2. Comparing those same targets with the Sloan Digital Sky Survey (SDSS), the relative flux differences between SDSS spectra and LAMOST spectra with the ASPSRC method are less than 10%, which underlines that the ASPSRC method is feasible for LAMOST flux calibration.

M Dwarf catalog of LAMOST general survey data release one

We present a spectroscopic catalog of 93 619 M dwarfs from the first data release of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) general survey. During sample selection, M giant contamination was eliminated using 2MASS photometry and CaH/TiO molecular indices. For each spectrum, the spectral subtype and values are provided including radial velocity, Hα equivalent width, a series of prominent molecular band indices, and the metal–sensitive parameter ζ, as well as distances and the space motions for high S/N objects. In addition, Hα emission lines are measured to examine the magnetic activity properties of M dwarfs and 7179 active ones are found. In particular, a subsample with significant variation in magnetic activity is revealed through observations from different epochs. Finally, statistical analysis for this sample is performed, including the metallicity classification, the distribution of molecular band indices and their errors.

A large sample of metallic-line star candidates from LAMOST Data Release 1

We present a sample of metallic-line star (Am) candidates from the Large sky Area Multi-Object ber 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 classied as A{type or early{F stars by both LAMOST pipeline and visual inspection. Then we make some analysis on this sample and nally 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 oers valuable material for the research on this type of chemically peculiar stars.

ON THE CONSTRUCTION OF A NEW STELLAR CLASSIFICATION TEMPLATE LIBRARY FOR THE LAMOST SPECTRAL ANALYSIS PIPELINE

The LAMOST spectral analysis pipeline, called the 1D pipeline, aims to classify and measure the spectra observed in the LAMOST survey. Through this pipeline, the observed stellar spectra are classified into different subclasses by matching with template spectra. Consequently, the performance of the stellar classification greatly depends on the quality of the template spectra. In this paper, we construct a new LAMOST stellar spectral classification template library, which is supposed to improve the precision and credibility of the present LAMOST stellar classification. About one million spectra are selected from LAMOST Data Release One to construct the new stellar templates, and they are gathered in 233 groups by two criteria: (1) pseudo g – r colors obtained by convolving the LAMOST spectra with the Sloan Digital Sky Survey ugriz filter response curve, and (2) the stellar subclass given by the LAMOST pipeline. In each group, the template spectra are constructed using three steps. (1) Outliers are excluded using the Local Outlier Probabilities algorithm, and then the principal component analysis method is applied to the remaining spectra of each group. About 5% of the one million spectra are ruled out as outliers. (2) All remaining spectra are reconstructed using the first principal components of each group. (3) The weighted average spectrum is used as the template spectrum in each group. Using the previous 3 steps, we initially obtain 216 stellar template spectra. We visually inspect all template spectra, and 29 spectra are abandoned due to low spectral quality. Furthermore, the MK classification for the remaining 187 template spectra is manually determined by comparing with 3 template libraries. Meanwhile, 10 template spectra whose subclass is difficult to determine are abandoned. Finally, we obtain a new template library containing 183 LAMOST template spectra with 61 different MK classes by combining it with the current library.

Comparison between MAFAGS-OS spectra and Kurucz-ODF spectra

Grids of theoretical stellar spectra are fundamental for estimating basic stellar parameters from photometric and spectroscopic data observed in large sky surveys such as SDSS, LAMOST, Gaia, etc. Do the different atmosphere models influence the parameters estimation? We compute the Lick indexes and uvby color indexes using the MAFAGS-OS grid of model atmospheres and fluxes provided by F. Grupp (personal comm.) and the Kurucz grids [1]. A spectrum comparison reveals the behavior of spectra from the MAFAGS and Kurucz grids. We find that using the (b-y) index, consistent effective temperatures can be determined from both the Kurucz and MAFAGS grids of theoretical spectra. The m1 index, together with color index, can be used to determine the metallicity of F- and G-type stars, but the measurements of the Kurucz and MAFAGS grids show systematic discrepancies for cool stars. The c1 indexes computed with both grids show small discrepancies for Teff 6000 K, the c1 indexes agree well. The Lick indexes of the Kurucz grid and the MAFAGS grid tend to be in agreement for warm stars with temperatures above 5000 K, while for cool stars with temperatures ranging from 4000 K to 5000 K, the difference of Lick indexes for both models is apparently large. We also compare the MAFAGS spectrum and Kurucz spectrum of the same temperature, surface gravity, and metallicity using a correlation coefficient for the complete spectrum. For warm stars, the MAFAGS and Kurucz spectra are almost the same, while for cool stars below 5000 K, there are some discrepancies between the MAFAGS and Kurucz spectra that induce internal discrepancies in the parameters determination.

Spectral classification and composites of galaxies in LAMOST DR4

We study the classification and composite spectra of galaxy in the fourth data release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). We select 40,182 spectra of galaxies from LAMOST DR4, which have photometric in- formation but no spectroscopic observations in the Sloan Digital Sky Survey(SDSS). These newly observed spectra are re-calibrated and classified into six classes, i.e. pas- sive, H{\alpha}-weak, star-forming, composite, LINER and Seyfert using the line intensity (H\b{eta}, [OIII]{\lambda}5007, H{\alpha} and [NII]{\lambda}6585). We also study the correlation between spectral classes and morphological types through three parameters: concentration index, (u - r) color, and D4000n index. We calculate composite spectra of high signal-to-noise ra- tio(S/N) for six spectral classes, and using these composites we pick out some features that can differentiate the classes effectively, including H\b{eta}, Fe5015, H{\gamma}A, HK, and Mg2 band etc. In addition, we compare our composite spectra with the SDSS ones and analyse their difference. A galaxy catalogue of 40,182 newly observed spectra (36,601 targets) and the composite spectra of the six classes are available online.

Carbon Stars Identified from LAMOST DR4 Using Machine Learning

In this work, we present a catalog of 2651 carbon stars from the fourth Data Release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST). Using an efficient machine-learning algorithm, we find out these stars from more than seven million spectra. As a by-product, 17 carbon-enhanced metal-poor (CEMP) turnoff star candidates are also reported in this paper, and they are preliminarily identified by their atmospheric parameters. Except for 176 stars that could not be given spectral types, we classify the other 2475 carbon stars into five subtypes including 864 C-H, 226 C-R, 400 C-J, 266 C-N, and 719 barium stars based on a series of spectral features. Furthermore, we divide the C-J stars into three subtypes of CJ( H), C-J(R), C-J(N), and about 90% of them are cool N-type stars as expected from previous literature. Beside spectroscopic classification, we also match these carbon stars to multiple broadband photometries. Using ultraviolet photometry data, we find that 25 carbon stars have FUV detections and they are likely to be in binary systems with compact white dwarf companions.