J/MNRAS/485/2167  M-type stars in LAMOST DR5 unclassified spectra  (Guo+, 2019)
Recognition of M-type stars in the unclassified spectra of LAMOST DR5 using a
hash-learning method.
    Guo Y.-X., Luo A.-L., Zhang S., Du B., Wang Y.-F., Chen J.-J., Zuo F.,
    Kong X., Hou Y.-H.
   <Mon. Not. R. Astron. Soc., 485, 2167-2178 (2019)>
   =2019MNRAS.485.2167G 2019MNRAS.485.2167G    (SIMBAD/NED BibCode)
ADC_Keywords: Spectroscopy ; Stars, M-type ; Stars, late-type ; Optical
Keywords: techniques: spectroscopic - stars: late-type - stars: low-mass
Abstract:
    Our study aims to recognize M-type stars which are classified as
    'UNKNOWN' due to poor quality in the Large sky Area Multi-Object fiber
    Spectroscopic Telescope (LAMOST) DR5 V1. A binary nonlinear hashing
    algorithm based on Multi-Layer Pseudo-Inverse Learning (ML-PIL) is
    proposed to effectively learn spectral features for M-type-star
    detection, which can overcome the bad fitting problem of template
    matching, particularly for low S/N spectra. The key steps and the
    performance of the search scheme are presented. A positive data set is
    obtained by clustering the existing M-type spectra to train the ML-PIL
    networks. By employing this new method, we find 11410 M-type spectra
    out of 642178 'UNKNOWN' spectra, and provide a supplemental catalogue.
    Both the supplemental objects and released M-type stars in DR5 V1 are
    composed of a whole M-type sample, which will be released in the
    official DR5 to the public in June 2019. All the M-type stars in the
    data set are classified as giants and dwarfs by two suggested
    separators: (1) a colour diagram of H versus J-K from 2MASS, (2) line
    indices CaOH versus CaH1, and the separation is validated with the
    Hertzsprung-Russell diagram (HRD) derived from Gaia DR2. The magnetic
    activities and kinematics of M dwarfs are also provided with the
    equivalent width (EW) of the Hα emission line and the
    astrometric data from Gaia DR2 respectively.
Description:
    LAMOST is a 4-m reflecting Schmidt telescope with a large field of
    view (FoV) of 5 degrees in diameter. It has 4000 fibres mounted on its
    focal plane and 16 spectrographs with 32 CCD cameras, so that it can
    simultaneously observe up to 4000 objects (Cui et al.
    2012RAA....12.1197C 2012RAA....12.1197C). The raw CCD data are reduced and analyzed by the
    LAMOST data pipelines, which consist of a 2D pipeline and a 1D
    pipeline. The primary functions of the 2D pipeline include bias
    calibration, flat-field correction, spectral extraction, sky
    subtraction, wavelength calibration, flux calibration, and
    sub-exposures combination. The calibrated spectra from the 2D pipeline
    are then fed to the 1D pipeline which performs spectral classification
    and parameter determination based on template matching and chi-square
    criteria (Luo et al. 2015RAA....15.1095L 2015RAA....15.1095L, Cat. V/146).
    By July 2017, LAMOST had completed its five-year regular survey. The
    LAMOST DR5 V1 includes 9017844 spectra of stars, galaxies, quasars,
    and unrecognized objects. These spectra cover the wavelength range
    from 3690 to 9100Å with a resolution of R∼1800 at the wavelength
    5500Å.
    Among the 9 million spectra in LAMOST DR5 V1, 642178 unrecognized
    spectra were labelled 'UNKNOWN'. During the classification process of
    the 1D pipeline, a spectrum is classified as 'UNKNOWN' if the
    confidence of the classification result is lower than a given
    threshold value. In this study we build a multilayer Pseudo-Inverse
    Learning (ML-PIL) to fulfil the hash-learning process, so as to search
    M-type stars in the 'UNKNOWN' spectra of LAMOST DR5 V1.
File Summary:
--------------------------------------------------------------------------------
 FileName      Lrecl  Records   Explanations
--------------------------------------------------------------------------------
ReadMe            80        .   This file
catalog.dat      388    11410   Supplemental catalogue of 11410 recognized
                                 M-type stars
--------------------------------------------------------------------------------
See also:
    V/164 : LAMOST DR5 catalogs (Luo+, 2019)
Byte-by-byte Description of file: catalog.dat
--------------------------------------------------------------------------------
   Bytes Format Units     Label     Explanations
--------------------------------------------------------------------------------
   1- 19  A19   ---       ID        LAMOST object ID (JHHMMSS.ss+DDMMSS.s)
  21- 30  A10   "Y:M:D"   ObsDate   LAMOST Target observation date
  32- 36  I5    d         MJD       Modified Julian Day
  38- 57  A20   ---       PlanId    LAMOST Plan Name
  59- 60  I2    ---       specId    LAMOST unique spectra ID
  62- 64  I3    ---       FiberId   LAMOST Fiber ID
  66- 76  F11.7 deg       RAdeg     Right ascension (J2000)
  78- 87  F10.7 deg       DEdeg     Declination (J2000)
  89- 94  F6.2  ---       SNR       Signal to noise ratio of r filter
  96- 97  A2    ---       subClass  Stellar Sub-Class
  99-106  F8.2  km/s      HRV       Heliocentric radial velocity
 108-114  F7.2  ---       EWHa      ? Equivalent width of Hα line
 116-123  F8.3  ---     e_EWHa      ? Error on EWHa
 125-129  F5.2  ---       TiO5      ? Spectral index of TiO5
 131-135  F5.2  ---       CaH2      ? Spectral index of CaH2
 137-141  F5.2  ---       CaH3      ? Spectral index of CaH3
 143-147  F5.2  ---       TiO1      ? Spectral index of TiO1
 149-153  F5.2  ---       TiO2      ? Spectral index of TiO2
 155-159  F5.2  ---       TiO3      ? Spectral index of TiO3
 161-166  F6.2  ---       TiO4      ? Spectral index of TiO4
 168-172  F5.2  ---       CaH1      ? Spectral index of CaH1
 174-179  F6.2  ---       CaOH      ? Spectral index of CaOH
 181-186  F6.3  ---     e_TiO5      ? Error on TiO5
 188-193  F6.3  ---     e_CaH2      ? Error on CaH2
 195-200  F6.3  ---     e_CaH3      ? Error on CaH3
 202-207  F6.3  ---     e_TiO1      ? Error on TiO1
 209-214  F6.3  ---     e_TiO2      ? Error on TiO2
 216-221  F6.3  ---     e_TiO3      ? Error on TiO3
 223-228  F6.3  ---     e_TiO4      ? Error on TiO4
 230-235  F6.3  ---     e_CaH1      ? Error on CaH1
 237-242  F6.3  ---     e_CaOH      ? Error on CaOH
 244-251  F8.2  ---       Na        ? Line index of Na line
 253-258  F6.2  ---       zeta      ? Metal-sensitive parameter
                                     (Yi et al. 2014AJ....147...33Y 2014AJ....147...33Y;
                                     Guo et al. 2015RAA....15.1182G 2015RAA....15.1182G,
                                     Cat. J/other/RAA/15.1182)
 260-266  F7.3  ---     e_zeta      ? Error on zeta
     268  I1    ---       Giant     Luminosity class (0 for dwarfs,
                                     1 for giants)
 270-277  F8.5  mas       plx       ? Parallax
 279-284  F6.4  mas     e_plx       ? Error on plx
 286-293  F8.3  mas/yr    pmRA      ? Proper motion in right ascension
 295-299  F5.3  mas/yr  e_pmRA      ? Error on pmRA
 301-308  F8.3  mas/yr    pmDE      ? Proper motion in declination
 310-314  F5.3  mas/yr  e_pmDE      ? Error on pmDE
 316-327  F12.2 pc        Dist      ? Distance in parsecs from the sun
 329-336  F8.2  km/s      U         ? Galactic space velocity, the direction
                                     towards the center of the galaxy is
                                     positive
 338-346  F9.2  km/s      V         ? Galactic space velocity, the direction
                                     towards the Milky Way's rotation is
                                     positive
 348-355  F8.2  km/s      W         ? Galactic space velocity, the direction
                                     towards the North Pole of the Milky Way
                                     is positive
 357-366  F10.2 pc        zgal      ? Verticle Distance from the plane
 368-377  F10.6 deg       GLON      ? Galactic Longtitude of the object
 379-388  F10.6 deg       GLAT      ? Galactic Latitude of the object
--------------------------------------------------------------------------------
History:
    From electronic version of the journal
(End)                                           Ana Fiallos [CDS]    19-Sep-2022