J/MNRAS/500/4849 GALAH emission-line stars (Cotar+, 2021)
The GALAH survey: characterization of emission-line stars with spectral
modelling using autoencoders.
Cotar K, Zwitter T., Traven G., Bland-Hawthorn J., Buder S., Hayden M.R.,
Kos J., Lewis G.F., Martell S. L., Nordlander T., Stello D., Horner J.,
Ting Y.-S., Zerjal M., GALAH collaboration
<Mon. Not. R. Astron. Soc. 500, 4849-4865 (2021)>
=2021MNRAS.500.4849C 2021MNRAS.500.4849C (SIMBAD/NED BibCode)
ADC_Keywords: Stars, emission; Stars, Be; Stars, peculiar; Spectroscopy
Keywords: line: profiles - methods: data analysis - catalogues -
stars: activity - stars: emission line, Be - stars: peculiar
Abstract:
We present a neural network autoencoder structure that is able to
extract essential latent spectral features from observed spectra and
then reconstruct a spectrum from those features. Because of the
training with a set of unpeculiar spectra, the network is able to
reproduce a spectrum of high signal-to-noise ratio that does not show
any spectral peculiarities, even if they are present in an observed
spectrum. Spectra generated in this manner were used to identify
various emission features among spectra acquired by multiple surveys
using the HERMES spectrograph at the Anglo-Australian telescope.
Emission features were identified by a direct comparison of the
observed and generated spectra. Using the described comparison
procedure, we discovered 10364 candidate spectra with varying
intensities (from partially filled-in to well above the continuum) of
the Hα/Hβ emission component, produced by different
physical mechanisms. A fraction of these spectra belong to the
repeated observation that shows temporal variability in their emission
profile. Among the emission spectra, we find objects that feature
contributions from a nearby rarefied gas (identified through the
emission of [NII] and [SII] lines) that was identified in 4004
spectra, which were not all identified as having Hα emission.
The positions of identified emission-line objects coincide with
multiple known regions that harbour young stars. Similarly, detected
nebular emission spectra coincide with visually prominent nebular
clouds observable in the red all-sky photographic composites.
Description:
We provide a list of 10364 candidate spectra with varying intensities
of the Hα/Hβ emission component. Among them we identified
4004 spectra with signs of nebular contribution, identified through
the emission of [NII] and [SII] lines.
File Summary:
--------------------------------------------------------------------------------
FileName Lrecl Records Explanations
--------------------------------------------------------------------------------
ReadMe 80 . This file
emigalah.dat 359 658919 Catalogue of all analysed objects
--------------------------------------------------------------------------------
See also:
J/MNRAS/478/4513 : GALAH Survey DR2 (Buder+, 2018)
http://galah-survey.org/ : GALAH home page
Byte-by-byte Description of file: emigalah.dat
--------------------------------------------------------------------------------
Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 19 I19 --- GaiaDR2 ?=- Gaia DR2 identifier, source_id
21- 35 I15 --- GALAH GALAH unique per observation id
37- 54 F18.14 deg RAdeg Right ascension from 2MASS (J2000)
56- 73 E18.15 deg DEdeg Declination from 2MASS (J2000)
75- 97 E23.20 0.1nm EWHa Hα equivalent width of a difference
between observed and template spectrum
99-121 E23.20 0.1nm EWHb Hβ equivalent width of a difference
between observed and template spectrum
123-144 F22.18 0.1nm EWHaabs Hα equivalent width of an absolute
difference between observed and template
spectrum
146-167 F22.18 0.1nm EWHbabs Hβ equivalent width of an absolute
difference between observed and template
spectrum
169-189 F21.16 km/s EWHaW10 Width of the Hα emission feature at 10%
of its peak flux amplitude
191-213 E23.20 --- EWHaasym Value of asymmetry index for the Hα line
215-237 E23.20 --- EWHbasym Value of asymmetry index for the Hβ line
239-243 A5 --- SB2-c3 [False True] Binarity detection in red arm
245-249 A5 --- SB2-c1 [False True] Binarity detection in blue arm
251 I1 --- NII [0-2] Number of detected [NII] peaks
253 I1 --- SII [0-2] Number of detected [SII] peaks
255-278 E24.20 0.1nm EWNII Equivalent width of a fitted Gaussian profiles
to the [NII] emission features
280-303 E24.20 0.1nm EWSII Same as the NII_EW, but for the [SII] doublet
305-326 E22.18 km/s RVNII Intrinsic radial velocity of the [NII] doublet
in the barycentric frame (1)
328-352 F25.19 km/s RVSII Same as rv_NII, but for the [SII] doublet
354 I1 --- Nebular [0/1] Is spectrum considered to have an
additional nebular component (1=True)
356 I1 --- Emiss [0/1] Is spectrum considered to have an
additional Hα emission component
(1=True)
358-359 I2 --- Flag Sum of all raised bitwise flags for a
spectrum (2)
--------------------------------------------------------------------------------
Note (1): To compute this, we subtracted radial velocity of a star
Note (2): Bitwise quality flags as follows:
0 = None of the flags was raised
1 = Wavelength solution (or determined radial velocity)
might be wrong in the blue arm of the spectrum.
2 = Wavelength solution (or determined radial velocity)
might be wrong in the red arm of the spectrum.
Determined from cross-correlation peak between
observed and reference spectra.
4 = Possible strong contamination by sky emission
features. 4 or more residual sky lines were detected.
Could be a result of under- or over-correction.
8 = The spectrum most likely contains duplicated
spectral absorption lines of a resolved SB2 binary
Binarity was detected in both arms
16 = Large difference between reference and observed
spectrum in the blue arm of a spectrum.
MSE was > 0.008.
32 = Large difference between reference and observed
spectrum in the red arm of a spectrum. Median
squared error (MSE) between them was > 0.002.
64 = Reference spectrum for the Hβ range does not exist.
128 = Reference spectrum for the Hα range does not exist.
--------------------------------------------------------------------------------
Acknowledgements:
Klemen Cotar, klemen.cotar(at)fmf.uni-lj.si
(End) Patricia Vannier [CDS] 11-Dec-2020