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arXiv · 1712.04476

Photometric redshifts for the next generation of deep radio continuum surveys - II. Gaussian processes and hybrid estimates

Kenneth J Duncan·Matt J. Jarvis·Michael J. I. Brown·Huub J. A. Rottgering
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Abstract

Building on the first paper in this series (Duncan et al. 2018), we present a study investigating the performance of Gaussian process photometric redshift (photo-z) estimates for galaxies and active galactic nuclei detected in deep radio continuum surveys. A Gaussian process redshift code is used to produce photo-z estimates targeting specific subsets of both the AGN population - infrared, X-ray and optically selected AGN - and the general galaxy population. The new estimates for the AGN population are found to perform significantly better at z > 1 than the template-based photo-z estimates presented in our previous study. Our new photo-z estimates are then combined with template estimates through hierarchical Bayesian combination to produce a hybrid consensus estimate that outperforms either of the individual methods across all source types. Photo-z estimates for radio sources that are X-ray sources or optical/IR AGN are signficantly improved in comparison to previous template-only estimates, with outlier fractions and robust scatter reduced by up to a factor of ~4. The ability of our method to combine the strengths of the two input photo-z techniques and the large improvements we observe illustrate its potential for enabling future exploitation of deep radio continuum surveys for both the study of galaxy and black hole co-evolution and for cosmological studies.

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Kenneth J Duncan, Matt J. Jarvis, Michael J. I. Brown, Huub J. A. Rottgering. 2018-04-12. Photometric redshifts for the next generation of deep radio continuum surveys - II. Gaussian processes and hybrid estimates. https://doi.org/10.1093/mnras%2Fsty940

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