The catalogues below were produced machine learning algorithms as described in Vincent et al. (2023). Details and column descriptions can be found in the paper.
The candidates catalogue contains about 1.3M Gaia DR3 objects for which the probability of being a white dwarf star was calculated using neural networks and various Gaia measurements, including magnitudes, distance and proper motions. This method offers a much more robust method than traditional approaches that select candidates from a Hertzsprung-Russel or color-color diagram, owing to the larger parameter space and the automatic feature detection. Gaia measurements relevant to the calculation of the probability of being a white dwarf are also included in the catalogue.
The Gaia-SDSS catalogue contains 36610 SDSS DR17 spectra that were cross-matched to high-probability white dwarfs in the candidates catalogue. The spectra were classified using neural networks trained on previous SDSS data releases. Included in the catalogue are the probability that the primary spectroscopic type of the object among 11 possible white dwarf or subdwarf types, the probability of having a main sequence companion (only for DA, DB, DC white dwarfs), along with all columns from the candidate catalogue. Note that some Gaia objects have had several spectra cross-matched with them.
The Gaia-SDSS catalogue is also available via the Montreal White Dwarf Database. Machine learning tools used in Vincent et al. (2023) can be found (and tried!) on the MWDD here.
In Vincent et al.(2023b), we have spectroscopically classified about 100,000 white dwarf XP spectra as one of six possible types (DA, DB, DC, DO, DQ, DZ), nearly tripling the number of white dwarfs with spectroscopic classification. We measured their physical parameters using synthetic SDSS photometry derived from XP spectra and, more importantly, class-appropriate model atmospheres. Our results recover the expected mass and temperature distributions obtained by higher-resolution spectroscopic studies for each spectral class. The description of the catalogue contents can be found on Table 3 of Vincent et al. (2023b).
We also provide the synthetic u-band corrections shown in Figure 6 of the paper, used to alleviate color-dependent calibration issues (see Section 4.1).The catalogue and u-band corrections can be downloaded below:
| GSPCWD_catalogue.csv |
| SdssStd_mag_u_corr_blue.csv (BP-RP<-0.15) |
| SdssStd_mag_u_corr_red.csv(BP-RP>-0.15) |
The Gaia XP catalogue will also available via the Montreal White Dwarf Database once it has gone through the review process.