KiDS-DR4 bright galaxy sample DL photo-z

This dataset, used as foreground for KiDS lensing and clustering studies, is flux-limited to r<20mag with mean z=0.23 and covers 1000deg^2^. Its photo-zs were previously derived with artificial neural networks from the ANNz2 package trained on the Galaxy And Mass Assembly (GAMA) spectroscopy.

Here we considerably improve over these previous redshift estimations by building a DL model, Hybrid-z, which combines an Inception-based convolutional neural network operating on four-band KiDS images with an artificial neural network using nine-band magnitudes from KiDS+VIKING. The Hybrid-z framework provides state-of-the-art photo-zs for KiDS-Bright, with negligible mean residuals of O(10^-4^) and scatter at the level of 0.014(1+z) - representing a reduction by 20% over the previous nine-band derivations with ANNz2.