J/A+A/682/A5 Gaia white dwarfs Classification (Vincent+, 2024)
Classification and parameterization of a large Gaia sample of white dwarfs
using XP spectra.
Vincent D., Barstow M.A., Jordan S., Mander C., Bergeron P., Dufour P.
<Astron. Astrophys. 682, A5 (2024)>
=2024A&A...682A...5V 2024A&A...682A...5V (SIMBAD/NED BibCode)
ADC_Keywords: Stars, white dwarf ; Photometry, SDSS ; Effective temperatures ;
Stars, masses
Keywords: techniques: spectroscopic - stars: fundamental parameters -
white dwarfs
Abstract:
The latest Gaia data release in July 2022, DR3, in addition to the
refinement of the astrometric and photometric parameters from DR2,
added a number of important data products to those available in
earlier releases, including radial velocity data, information on
stellar multiplicity, and XP spectra of a selected sample of stars.
Gaia has proved to be an important search tool for white dwarf stars,
which are readily identifiable from their absolute G magnitudes as low
luminosity objects in the Hertzsprung-Russell (H-R) diagram. Each data
release has yielded large catalogs of white dwarfs, containing several
hundred thousand objects, far in excess of the numbers known from all
previous surveys (∼40,000). While the normal Gaia photometry (G, GBP,
and GRP bands) and astrometry can be used to identify white dwarfs
with high confidence, it is much more difficult to parameterize the
stars and determine the white dwarf spectral type from this
information alone. Observing all stars in these catalogs with
follow-up spectroscopy and photometry is also a huge logistical
challenge with current facilities.
The availability of the XP spectra and synthetic photometry presents
an opportunity for a more detailed spectral classification and
measurement of the effective temperature and surface gravity of Gaia
white dwarfs.
A magnitude limit of G<17.6 was applied to the routine production of
XP spectra for Gaia sources, which would have excluded most white
dwarfs. Therefore, we created a catalog of 100000 high-quality white
dwarf identifications for which XP spectra were processed, with a
magnitude limit of G<20.5. Synthetic photometry was computed for all
these stars, from the XP spectra, in Johnson, SDSS, and J-PAS,
published as the Gaia Synthetic Photometry Catalog - White Dwarfs
(GSPC-WD). We took this catalog and applied machine learning
techniques to provide a classification of all the stars from the XP
spectra. We have then applied an automated spectral fitting program,
with chi-squared minimization, to measure their physical parameters
(effective temperature and log_g) from which we could estimate the
white dwarf masses and radii.
We present the results of this work, demonstrating the power of being
able to classify and parameterize such a large sample of ∼100000
stars. We describe what we can learn about the white dwarf population
from this dataset. We also explored the uncertainties in the process
and the limitations of the dataset.
Description:
We have taken the Gaia Synthetic Photometry catalogue of white dwarfs
(GSPC-WD) and used the original XP spectra, from which the synthetic
photometry were derived, to provide a more detailed classification of
the white dwarfs into six spectral types (DA, DB, DO, DC, DQ and DZ).
Using these spectral classifications we then determined the physical
parameters, effective temperature and surface gravity, using an
automatic spectral fitting programme. From these parameters, we also
determined the white dwarf mass and luminosity. We now make available
a new white dwarf catalogue which contains the results of this work.
The catalogue includes the most likely spectral type, SDSS magnitudes
and fluxes, effective temperature, log surface gravity, white dwarf
mass and luminosity, along with their errors.
We also include the classification probability for each spectral type.
During this work we identified some remaining discrepancies between
the Gaia synthetic u and SDSS u band photometry, for which we
corrected. The u-band correction and its error are included in this
catalogue. For some stars the u-band flux is negligible (not
detected). In those cases the magnitude and flux error are set to
-999.0 and the u-band correction and its error set to 0.0. Valid
results from the spectral fitting could not be obtained for all stars.
In those cases the values in the physical parameters columns are set
to -999.0.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
catalog.dat 338 100886 Gaia WD DR3 XP-classification catalogue
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See also:
I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)
Byte-by-byte Description of file: catalog.dat
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Bytes Format Units Label Explanations
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1- 19 I19 --- GaiaDR3 The unique Gaia DR3 source identifier
21- 23 A3 --- SpType WD spectral type
25- 33 F9.4 mag umag ?=-999 Synthetic SDSS u magnitude
35- 41 F7.4 mag gmag Synthetic SDSS g magnitude
43- 49 F7.4 mag rmag Synthetic SDSS r magnitude
51- 57 F7.4 mag imag Synthetic SDSS i magnitude
59- 67 F9.4 mag zmag ?=-999 Synthetic SDSS z magnitude
69- 90 E22.17 W/m2/nm e_Fluxu ?=-999 Synthetic SDSS u flux error
92-113 E22.17 W/m2/nm e_Fluxg Synthetic SDSS g flux error
115-136 E22.17 W/m2/nm e_Fluxr Synthetic SDSS r flux error
138-159 E22.17 W/m2/nm e_Fluxi Synthetic SDSS i flux error
161-182 E22.17 W/m2/nm e_Fluxz Synthetic SDSS z flux error
184-187 F4.2 --- PDA DA classification probability
189-192 F4.2 --- PDB DB classification probability
194-197 F4.2 --- PDC DC classification probability
199-202 F4.2 --- PDO DO classification probability
204-207 F4.2 --- PDQ DQ classification probability
209-212 F4.2 --- PDZ DZ classification probability
214-219 I6 K Teff ?=-999 Effective temperature
221-228 F8.3 [cm/s2] logg ?=-999 Logarithm of surface gravity
230-237 F8.3 Msun M ?=-999 Mass
239-244 I6 K e_Teff ?=-999 Error on the effective temperature
246-253 F8.3 [cm/s2] e_logg ?=-999 Error on the surface gravity
255-263 F9.3 Msun e_M ?=-999 Error on the mass
265-273 F9.4 mag umagcor ?=-999 u band correction
275-283 F9.4 mag e_umagcor []?=-999 u band correction error
285-311 A27 --- comp Model atmosphere composition
313-318 F6.3 --- logCHe Carbon abundance for DQ stars
320-328 F9.4 [Lsun] logL ?=-999 Log of the luminosity
330-338 F9.4 [Lsun] e_logL []?=-999 Error on the Log luminosity
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Acknowledgements:
Claudio Pagani, cp232(at)leicester.ac.uk
(End) Patricia Vannier [CDS] 15-Dec-2023