12.2.2 galaxy_candidates table
The galaxy_candidates table gathers products addressing the classification and characterisation of sources identified as galaxy candidates. The name ‘galaxy’ is used here as a generic term but the nature of the sources covered by a given DPAC module will vary depending on the type of product, covering among other things AGNs.
This table integrates sources stemming from various processing modules and the exact selection rules applied to the outputs of these modules are specified in Table 12.4. The table population logic is the same as for the qso_candidates table.
Similar to the qso_candidates table, the bit field source_selection_flags can be used to isolate those sources originally selected based on the eligibility rules of a given module. Section 12.5 also gives hints about how this field and others can be used in ADQL queries.
The on-board source acquisition rules of Gaia will also impact the capability to detect and record galaxies, especially if they are extended compared to the pixel and PSF sizes. This will particularly affect sources with a resolved disk – see also Chapter 9 and de Bruijne et al. (2015). An indirect effect of this relates to potentially poorer astrometry achieved for extended sources. This is illustrated in the number of sources classified as galaxies by DSC: only a third of them features parallaxes and proper motion, against nearly 91% of those sources classified as quasar.
|Surface brightness||All sources produced by Surface brightness module selected|
|DSC||‘galaxy’ probability of any of the three DSC classifiers being greater than 0.5|
|UGC||All sources considered acceptable by UGC (Section 11.3.13)|
The outcome of this selection results in the following sources and products from the respective contributing modules:
Sources for which the Surface brightness as observed by Gaia has been analysed and fitted as described in Chapter 9. About a million of such sources are present in the table. For those, morphological parameters are provided following two possible source profile models: Sérsic and de Vaucouleurs. Finally, an additional flag provides further information about the processing status for each of the fitted profiles (flags_sersic and flags_de_vaucouleurs). In the rest of this chapter, this sample is referred to as the ‘Surface brightness’ sample.
Sources classified as ‘galaxy’ by any of the DSC classifiers (‘Allosmod’, ‘Specmod’, or their combination in ‘Combmod’). As explained in Section 11.3.2, the corresponding selection favours completeness over purity. As such, about 3.7 million sources stem from the results of this classification. In the galaxy_candidates table, a class label (classlabel_dsc) is provided but it should be borne in mind that it corresponds to that of the ‘Combmod’ classifier only. As such there are about 160 thousand fewer sources having this particular class label set to ‘galaxy’ than sources considered eligible by DSC in the table overall. Likewise, the two tabulated classification probabilities (classprob_dsc_combmod_galaxy and classprob_dsc_combmod_quasar) are those of the ‘Combmod’ classifier only. In the rest of this chapter, this sample is referred to as the ‘DSC’ sample. For science cases requiring a purer dataset, an additional class label was computed and tabulated as classlabel_dsc_joint. We hereafter refer to this sample as ‘DSC-Joint’. Finally, note that the two class probabilities hosted in the galaxy_candidates table are also provided with the DSC results provided in the top-level astrophysical_parameters table .
Sources for which a reliable spectroscopic redshift was computed by the UGC algorithm based on the BP/RP low-resolution spectra, as described in Section 11.3.13. This amounts to about 1.3 million sources having a redshift provided in the table (redshift_ugc). Unlike for the QSOC module providing the redshifts of the qso_candidates, there is no UGC redshift provided for sources that do not honour the UGC selection rules. In the rest of this chapter, this sample is referred to as the ‘UGC’ sample.
Sources classified as ‘GALAXY’ by a classifier based on the analysis of photometric lightcurves, and described in Section 10.3. For these both a class label (vari_best_class_name) and a class probability (vari_best_class_score) are provided. Details about how these are computed are given in Section 10.3. This classification contributes to about 2.5 million sources. In the rest of this chapter, this sample is referred to as the ‘Vari-Classification’ sample. Contrary to what happens in the qso_candidates table, these classification results are exclusive to the galaxy_candidates table and are not present in the vari_classifier_result table.
The class label of sources classified in Self-Organised Maps (SOM) by the OA module described in Section 11.3.12 is tabulated in classlabel_oa. This information is in principle redundant with that provided in the oa_neuron_information table, but it is here limited to those sources selected through the other modules listed above. As such, there are many other sources labelled as extragalactic by OA that did not end up in galaxy_candidates, and these are discussed in Section 11.3.12. In the rest of this chapter, this sample is referred to as the ‘OA’ sample.
Similar to the qso_candidates table, a companion table galaxy_catalogue_name is provided that complements the information in the Surface brightness analysis. In this case, only one input catalogue was used and it is described in Krone-Martins et al. (2022). See Section 9.2 for further details.
The galaxy_candidates table contains 4 842 342 entries in Gaia DR3. Many of them overlap between the modules listed above, but a significant fraction of those is also unique to a given module. Table 12.5 gives an overview of the sources contributed by each module, and their overlaps are indicated in Table 12.6. Section 12.3 provides further statistics about the source distribution among modules.
|Surface brightness||914 837||914 837|
|Vari-Classification||2 451 364||2 477 273|
|DSC||3 726 548||4 841 799|
|UGC||1 367 153||1 367 153|
|OA||N/A||1 901 026|