Gaia Catalogue of Synthetic Photometry - White Dwarfs (GCSP-WD)

GSPC-WD catalogue 

This catalogue contains objects described in detail in Gaia Collaboration, Montegriffo et al., 2022, A&A, in press. The description of the catalogue from the paper is given below.

We have made the GSPC-WD synthetic photometry available
as a stand-alone catalogue27, including SDSS, JKC and JPLUS
XPSP and the DA classification probability. The photometry
of the individual J-PAS bands, used in the random forest
analysis, is not included due to their low signal-to-noise. For
WDs classified in SDSS, a subset of which were used in the
training/validation of the random forest algorithim, we also include
the full SDSS classifications as a separate column in the
GSPC-WD catalogue table. When the synthetic spectral bands are very narrow a
significant number of sources will have low signal-to-noise. Furthermore,
at the edges of the Gaia spectral range, away from
the peak of the effective area, this is also true for some stars
in the wider bands included in the catalogue. In some extreme
cases, there is no significant detection of the object. The random
forest algorithm is only able to classify a WD when valid
flux measurements are available for every photometric band we
include in the analysis. Therefore, no classification is recorded
in the catalogue when data for one or more bands is "missing".
In total 15,003 WDs from the total sample of 101,783 are not
classified. For completeness, we have made all the flux measurements
and corresponding magnitudes available for all objects in
the GSPC-WD. Hence magnitude/fluxes with very large errors,
up to several times the flux itself, are included. However, where
fluxes are negative, the magnitudes are not defined. When using
the catalogue, appropriate signal-to-noise cuts are advisable for
the specific work in-hand, to ensure data quality.

Total number of objects = 101,786; Format 1 object per row, 73 columns of data as listed below.

Column  Description of contents
1    Gaia source_id
2    ra
3    ra_error
4    dec
5    dec_error
6    JohnsonStd_mag_U
7    JohnsonStd_mag_B
8    JohnsonStd_mag_V
9    JohnsonStd_mag_R
10    JohnsonStd_mag_I
11    JohnsonStd_flux_U
12    JohnsonStd_flux_B
13    JohnsonStd_flux_V
14    JohnsonStd_flux_R
15    JohnsonStd_flux_I
16    JohnsonStd_flux_error_U
17    JohnsonStd_flux_error_B
18    JohnsonStd_flux_error_V
19    JohnsonStd_flux_error_R
20    JohnsonStd_flux_error_I
21    SdssStd_mag_u
22    SdssStd_mag_g
23    SdssStd_mag_r
24    SdssStd_mag_i
25    SdssStd_mag_z
26    SdssStd_flux_u
27    SdssStd_flux_g
28    SdssStd_flux_r
29    SdssStd_flux_i
30    SdssStd_flux_z
31    SdssStd_flux_error_u
32    SdssStd_flux_error_g
33    SdssStd_flux_error_r
34    SdssStd_flux_error_i
35    SdssStd_flux_error_z
36    Jplus_mag_uJAVA
37    Jplus_mag_J0378
38    Jplus_mag_J0395
39    Jplus_mag_J0410
40    Jplus_mag_J0430
41    Jplus_mag_gJPLUS
42    Jplus_mag_J0515
43    Jplus_mag_rJPLUS
44    Jplus_mag_J0660
45    Jplus_mag_iJPLUS
46    Jplus_mag_J0861
47    Jplus_mag_zJPLUS
48    Jplus_flux_uJAVA
49    Jplus_flux_J0378
50    Jplus_flux_J0395
51    Jplus_flux_J0410
52    Jplus_flux_J0430
53    Jplus_flux_gJPLUS
54    Jplus_flux_J0515
55    Jplus_flux_rJPLUS
56    Jplus_flux_J0660
57    Jplus_flux_iJPLUS
58    Jplus_flux_J0861
59    Jplus_flux_zJPLUS
60    Jplus_flux_error_uJAVA
61    Jplus_flux_error_J0378
62    Jplus_flux_error_J0395
63    Jplus_flux_error_J0410
64    Jplus_flux_error_J0430
65    Jplus_flux_error_gJPLUS
66    Jplus_flux_error_J0515
67    Jplus_flux_error_rJPLUS
68    Jplus_flux_error_J0660
69    Jplus_flux_error_iJPLUS
70    Jplus_flux_error_J0861
71    Jplus_flux_error_zJPLUS
72    probability DA
73    SDSS WD type