VizieR Online Data Catalog: Photometric SFR using machine learning (Delli Veneri+, 2019)

Abstract

This catalogue contains SFRs for 27,513,324 galaxies of the SDSS-DR7. To produce the catalogue, we started by querying the Galaxy View4 of the SDSS-DR7 for all the needed photometric features of galaxies with a "good" photometry (see PhotoFlags) and containing no Missing Values. We then applied the magnitudes cuts of our knowledge base (in order to keep the photometric features within the ranges of our knowledge base) and cross-matched the resulted data set with the photoz catalogue derived by Brescia et al. (2014b), in order to use them as a quality flag. The final catalogue contains the following columns: <P />Identifiers: dr9objid, objid, ra, dec, i.e. respectively, the object identifier in the SDSS DR9 and DR7 and their ascension and declination coordinates; <P />Quality flags: photoz and Quality_Flag, i.e. the photometric redshifts measured by Brescia et al. (2014b) and the associated flag. The Quality_Flag can assume three values 1, 2, and 3; 1 stands for the best photo-z accuracy, 2 and 3 for decreasing accuracy; <P />SFR: It is computed by the MLPQNA model with the 32 best features selected by the PHILAB method (excluding redshifts). <P />In order to select only SFRs with high-quality (i.e. only select sources inside the training set parameter space constrains), the user should impose photoz=0.33 and Quality_Flag=1. This is due by considering that in our knowledge base there are only objects with spectroscopic redshift less than 0.33, thus we are able to predict SFRs only for objects within such redshift range. These constraints will select ~6.6 million objects. Since we do not have any spectroscopic redshifts for the catalogue objects, we must use photometric redshifts (where available) to perform these cuts. Nevertheless using photometric redshifts instead of spectroscopic ones may introduce some contamination in the catalogue, i.e. a source may be inside the photoz=0.33 cut when in reality it has a spectroscopic redshift higher than 0.33. To estimate the number of such contaminants, we verify that among the 871 784 objects with photoz=0.33 and a spectroscopic redshift only ~1.33 per cent resulted to have a true redshift higher that 0.33. <P />(1 data file).