DOI: 10.5281/zenodo.6637716
title: Gaia Catalogue of Synthetic Photometry - White Dwarfs (GCSP-WD)

description: 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<br> as a stand-alone catalogue27, including SDSS, JKC and JPLUS<br> XPSP and the DA classification probability. The photometry<br> of the individual J-PAS bands, used in the random forest<br> analysis, is not included due to their low signal-to-noise. For<br> WDs classified in SDSS, a subset of which were used in the<br> training/validation of the random forest algorithim, we also include<br> the full SDSS classifications as a separate column in the<br> GSPC-WD catalogue table. When the synthetic spectral bands are very narrow a<br> significant number of sources will have low signal-to-noise. Furthermore,<br> at the edges of the Gaia spectral range, away from<br> the peak of the effective area, this is also true for some stars<br> in the wider bands included in the catalogue. In some extreme<br> cases, there is no significant detection of the object. The random<br> forest algorithm is only able to classify a WD when valid<br> flux measurements are available for every photometric band we<br> include in the analysis. Therefore, no classification is recorded<br> in the catalogue when data for one or more bands is "missing".<br> In total 15,003 WDs from the total sample of 101,783 are not<br> classified. For completeness, we have made all the flux measurements<br> and corresponding magnitudes available for all objects in<br> the GSPC-WD. Hence magnitude/fluxes with very large errors,<br> up to several times the flux itself, are included. However, where<br> fluxes are negative, the magnitudes are not defined. When using<br> the catalogue, appropriate signal-to-noise cuts are advisable for<br> 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<br> 1 Gaia source_id<br> 2 ra<br> 3 ra_error<br> 4 dec<br> 5 dec_error<br> 6 JohnsonStd_mag_U<br> 7 JohnsonStd_mag_B<br> 8 JohnsonStd_mag_V<br> 9 JohnsonStd_mag_R<br> 10 JohnsonStd_mag_I<br> 11 JohnsonStd_flux_U<br> 12 JohnsonStd_flux_B<br> 13 JohnsonStd_flux_V<br> 14 JohnsonStd_flux_R<br> 15 JohnsonStd_flux_I<br> 16 JohnsonStd_flux_error_U<br> 17 JohnsonStd_flux_error_B<br> 18 JohnsonStd_flux_error_V<br> 19 JohnsonStd_flux_error_R<br> 20 JohnsonStd_flux_error_I<br> 21 SdssStd_mag_u<br> 22 SdssStd_mag_g<br> 23 SdssStd_mag_r<br> 24 SdssStd_mag_i<br> 25 SdssStd_mag_z<br> 26 SdssStd_flux_u<br> 27 SdssStd_flux_g<br> 28 SdssStd_flux_r<br> 29 SdssStd_flux_i<br> 30 SdssStd_flux_z<br> 31 SdssStd_flux_error_u<br> 32 SdssStd_flux_error_g<br> 33 SdssStd_flux_error_r<br> 34 SdssStd_flux_error_i<br> 35 SdssStd_flux_error_z<br> 36 Jplus_mag_uJAVA<br> 37 Jplus_mag_J0378<br> 38 Jplus_mag_J0395<br> 39 Jplus_mag_J0410<br> 40 Jplus_mag_J0430<br> 41 Jplus_mag_gJPLUS<br> 42 Jplus_mag_J0515<br> 43 Jplus_mag_rJPLUS<br> 44 Jplus_mag_J0660<br> 45 Jplus_mag_iJPLUS<br> 46 Jplus_mag_J0861<br> 47 Jplus_mag_zJPLUS<br> 48 Jplus_flux_uJAVA<br> 49 Jplus_flux_J0378<br> 50 Jplus_flux_J0395<br> 51 Jplus_flux_J0410<br> 52 Jplus_flux_J0430<br> 53 Jplus_flux_gJPLUS<br> 54 Jplus_flux_J0515<br> 55 Jplus_flux_rJPLUS<br> 56 Jplus_flux_J0660<br> 57 Jplus_flux_iJPLUS<br> 58 Jplus_flux_J0861<br> 59 Jplus_flux_zJPLUS<br> 60 Jplus_flux_error_uJAVA<br> 61 Jplus_flux_error_J0378<br> 62 Jplus_flux_error_J0395<br> 63 Jplus_flux_error_J0410<br> 64 Jplus_flux_error_J0430<br> 65 Jplus_flux_error_gJPLUS<br> 66 Jplus_flux_error_J0515<br> 67 Jplus_flux_error_rJPLUS<br> 68 Jplus_flux_error_J0660<br> 69 Jplus_flux_error_iJPLUS<br> 70 Jplus_flux_error_J0861<br> 71 Jplus_flux_error_zJPLUS<br> 72 probability DA<br> 73 SDSS WD type