Meng-Xin Wang

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.

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.

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.

Nearby M subdwarfs from LAMOST data release 2

We identify 108 M subdwarfs(sd Ms) out of more than two hundred thousand M type spectra from the second data release(DR2) of the LAMOST regular survey. This sample, among which 58 members are identified for the first time, includes 33 extreme subdwarfs(esd Ms) and 11 ultra subdwarfs(usd Ms).The selection is based on the usual ratio of absorption depth of Ca H2, Ca H3 and TiO 5 band systems.We also emphasize the use of the Ca H1 band. We provide estimates of spectral subtype(SPT), L′epine metallicity index ζ, effective temperature and [Fe/H]. Both ζ–[Fe/H] and SPT–Teff figures show reasonable consistency; compared to PHOENIX model spectra, average rounded values of [Fe/H] for sd Ms, esd Ms and usd Ms are respectively –0.5, –1 and –1.5. The photometric distances are estimated, indicating that most sources are located within 500 pc of the Sun and 350 pc of the Galactic disk. Velocities and 3D Galactic motions are also briefly discussed. Among the 108 subdwarfs, seven stars appear to be active with a significant Hα emission line. The source LAMOST J104521.52+482823.3 is a white dwarf- M subdwarf binary, while LAMOST J123045.52+410943.8, also active, exhibits carbon features in red.

ISOTOPIC RATIOS OF 18O/17O IN THE GALACTIC CENTRAL REGION

The O-18/O-17 isotopic ratio of oxygen is a crucial measure of the secular enrichment of the interstellar medium by ejecta from high-mass versus intermediate-mass stars. So far, however, there is a lack of data, particularly from the Galactic center (GC) region. Therefore, we have mapped typical molecular clouds in this region in the J = 1-0 lines of (CO)-O-18 and (CO)-O-17 with the Delingha 13.7 m telescope (DLH). Complementary pointed observations toward selected positions throughout the GC region were obtained with the IRAM 30 m and Mopra 22 m telescopes. (CO)-O-18/(CO)-O-17 abundance ratios reflecting the O-18/O-17 isotope ratios were obtained from integrated intensity ratios of (CO)-O-18 and (CO)-O-17. For the first time, (CO)-O-18/(CO)-O-17 abundance ratios are determined for Sgr C (V similar to-58 km s(-1)), Sgr D (V similar to 80 km s(-1)), and the 1 degrees.3 complex (V similar to 80 km s(-1)). Through our mapping observations, abundance ratios are also obtained for Sgr A (similar to 0 and similar to 50 km s(-1) component) and Sgr B2 (similar to 60 km s(-1)), which are consistent with the results from previous single-point observations. Our frequency-corrected abundance ratios of the GC clouds range from 2.58 +/- 0.07 (Sgr D, V similar to 80 km s(-1), DLH) to 3.54 +/- 0.12 (Sgr A, similar to 50 km s(-1)). In addition, strong narrow components (line width less than 5 km s(-1)) from the foreground clouds are detected toward Sgr D (-18 km s(-1)), the 1 degrees.3 complex (-18 km s(-1)), and M+ 5.3-0.3 (22 km s(-1)), with a larger abundance ratio around 4.0. Our results show a clear trend of lower (CO)-O-18/(CO)-O-17 abundance ratios toward the GC region relative to molecular clouds in the Galactic disk. Furthermore, even inside the GC region, ratios appear not to be uniform. The low GC values are consistent with an inside-out formation scenario for our Galaxy.

LAMOST fiber unit positional precision passive detection exploiting the technique of template matching

The large sky area multi-object fiber spectroscopic telescope (LAMOST) is an innovative reflecting schmidt telescope, promising a very high spectrum acquiring rate of several ten-thousands of spectra per night. By using the parallel controllable fiber positioning technique, LAMOST makes reconfiguration of fibers accurately according to the positions of objects in minutes and fine adjusting the fibers. As a key problem, High precision positioning detection of LAMOST fiber positioning unit has always been highly regarded and some detection schemes have been proposed. Among these, active detection method, which determines the final accurate position of optical fiber end with the help of lighting the fiber, has been most widely researched, but this kind of method could not be applied in LAMOST real-time observation because it needs projecting light into fiber. A novel detection idea exploiting the technique of template matching is presented in this paper. As we know, final position of a specific fiber end can be easily inferred by its corresponding revolving angles of the central revolving axle and bias revolving axle in double revolving style, so the key point in this problem is converted to the accurate determination of these revolving angles. Template matching technique are explored to acquire the matching parameters for its real-time collected imagery, and thus determine the corresponding revolving angle of the central revolving axle and bias revolving axle respectively. Experiments results obtained with data acquired from LAMOST site are used to verify the feasibility and effectiveness of this novel method.

Spectroscopic Identification and Chemical Distribution of HII Regions in the Galactic Anti-center Area from LAMOST

We spectroscopically identify 101 Galactic HII regions using spectra from the Large Sky Area Multi- Object Fiber Spectroscopic Telescope (LAMOST) survey, cross-matched with an HII region catalog derived from the all-sky Wide-Field Infrared Survey Explorer(WISE) data. Among all HII regions in our sample, 47 sources are newly confirmed. Spatially, most of our identified HII regions are located in the anti-center area of the Galaxy. For each of the HII regions, we accurately extract and measure the nebular emission lines of the spectra, and estimate the oxygen abundances using the strong-line method. We focus on the abundance distribution of HII regions in the Galactic anti-center area. Accordingly, we derive the oxygen abundance gradient with a slope of -0.036 +/-0.004 dex/kpc, covering a range of RG from 8.1 to 19.3 kpc. In particular, we also fit the outer disk objects with a slope of -0.039 +/- 0.012 dex /kpc, which indicates that there is no flattening of the radial oxygen gradient in the outer Galactic disk.

Research on key problems for LAMOST optical fiber detection system

The large sky area multi-object fiber spectroscopic telescope (LAMOST) is an innovative reflecting schmidt telescope, promising a very high spectrum acquiring rate of several ten-thousands of spectra per night. By using the parallel controllable fiber positioning technique, LAMOST makes reconfiguration of fibers accurately according to the positions of objects in minutes and fine adjusting the fibers. During telescope observation period, each optical fiber unit positional accuracy directly determines the quality of subsequent spectrum acqusition, yet for real-time optical fiber positional accuracy, there only exists an internal information feedback which focus on the corresponding stepper motor driving conditions, however, this available information is not comprehensive, it can not offer the actual positional information for each fiber unit. Considering the LAMOST on-site environment, a novel real-time optical fiber positional accuracy detection system which can be integrated in the existing observation and control system need to be developed to solve this problem. During the observation interval, this system can offer a comprehensive and effective information feedback about the focal optical fiber positional accuracy. Based on this feedback, the observation assistants can properly adjust the observation strategies to ensure the effectiveness and accuracy of acquired spectrum. Furthermore, this fiber positional accuracy feedback can provide prior spectral quality information to the spectral processing personnel and optimal the spectrum processing efficiency.