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We show that mid-infrared data from the all-sky WISE survey can be used as a robust photometric redshift indicator for powerful radio AGN, in the absence of other spectroscopic or multi-band photometric information. Our work is motivated by a desire to extend the well-known K-z relation for radio galaxies to the wavelength range covered by the all-sky WISE mid-infrared survey. Using the LARGESS radio spectroscopic sample as a training set, and the mid-infrared colour information to classify radio sources, we generate a set of redshift probability distributions for the hosts of high-excitation and low-excitation radio AGN. We test the method using spectroscopic data from several other radio AGN studies, and find good agreement between our WISE-based redshift estimates and published spectroscopic redshifts out to z ~ 1 for galaxies and z ~ 3-4 for radio-loud QSOs. Our chosen method is also compared against other classification methods and found to perform reliably. This technique is likely to be particularly useful in the analysis of upcoming large-area radio surveys with SKA pathfinder telescopes, and our code is publicly available. As a consistency check, we show that our WISE-based redshift estimates for sources in the 843 MHz SUMSS survey reproduce the redshift distribution seen in the CENSORS study up to z ~ 2. We also discuss two specific applications of our technique for current and upcoming radio surveys; an interpretation of large scale HI absorption surveys, and a determination of whether low-frequency peaked spectrum sources lie at high redshift.
Accurate photometric redshifts are a lynchpin for many future experiments to pin down the cosmological model and for studies of galaxy evolution. In this study, a novel sparse regression framework for photometric redshift estimation is presented. Sim
Future radio surveys will generate catalogues of tens of millions of radio sources, for which redshift estimates will be essential to achieve many of the science goals. However, spectroscopic data will be available for only a small fraction of these
Machine learning techniques, specifically the k-nearest neighbour algorithm applied to optical band colours, have had some success in predicting photometric redshifts of quasi-stellar objects (QSOs): Although the mean of differences between the spect
We cross-match the two currently largest all-sky photometric catalogs, mid-infrared WISE and SuperCOSMOS scans of UKST/POSS-II photographic plates, to obtain a new galaxy sample that covers 3pi steradians. In order to characterize and purify the extr
Although the radio emission from most quasars appears to be associated with star forming activity in the host galaxy, about ten percent of optically selected quasars have very luminous relativistic jets apparently powered by a SMBH which is located a