TOPz: Photometric redshifts using template fitting applied to the GAMA survey

Abstract

Context. Accurate photometric redshift estimation is crucial for cosmological and galaxy evolution studies, especially with the advent of large-scale photometric surveys. Aims. We developed a photo-z estimation code called TOPz (Tartu Observatory Photo-z) and applied it to the GAMA photometric catalogue. Using nine-band photometric data from the GAMA project, we assessed the accuracy of TOPz by comparing its photo-z estimates to available spectroscopic redshifts from GAMA and DESI. The latter extends to z < 2 and m_Z < 24, allowing the photo-z accuracy to be validated beyond the GAMA limits. Methods. TOPz employs a Bayesian template-fitting approach to estimate photo-z from marginalised redshift posteriors. We generated synthetic galaxy spectra using the CIGALE software and ran template set optimisation. We improved the photometry by applying flux and flux uncertainty corrections. An analytical prior was then imposed on the resulting posteriors to refine the redshift estimates. Results. The photo-z estimates produced by TOPz show good agreement with the spectroscopic redshifts in the low-redshift regime (z < 0.5). We demonstrate the redshift accuracy across various magnitude bins and tested how the flux corrections and posteriors reflect the actual uncertainty of the estimates. For the GAMA sample, the sigma_NMAD = 0.012 for m_Z <18 and increases to sigma_NMAD = 0.021 for m_Z >19. The outlier fraction (|dz|/(1 + z)>0.1) in the same magnitude bins increases from 1% to 5%. We show that the TOPz results are consistent with those obtained from other photo-z codes (EAZY and SFM) applied to the same data set. Conclusions. TOPz is an advanced photo-z estimation code that integrates flux corrections, physical priors, and template set optimisation to provide state-of-the-art photo-z among competing template-based redshift estimators.

24 pages, 30 figures, accepted for publication in A&A

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