TOPz: photometric redshifts using template fitting applied to GAMA survey (2503.24039v1)

Abstract: Context. Accurate photometric redshift (photo-z) estimation is crucial for cosmological and galaxy evolution studies, especially with the advent of large-scale photometric surveys. Aims. We develop a photo-z estimation code called TOPz (Tartu Observatory Photo-z) and apply it to the GAMA photometric catalogue. Methods. TOPz employs a Bayesian template-fitting approach to estimate photo-z from marginalised redshift posteriors. Using nine-band photometric data from the GAMA project, we assess the accuracy of TOPz by comparing its photo-z estimates to available spectroscopic redshifts. We generate synthetic galaxy spectra using the CIGALE software and run template set optimisation. We improve the photometry by applying flux and flux uncertainty corrections. An analytical prior is 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. We demonstrate the redshift accuracy across various magnitude bins and test how the flux corrections and posteriors reflect the actual uncertainty of the estimates. We show that the TOPz results are consistent with those obtained from other photo-z codes applied to the same data set. Additionally, TOPz estimates stellar masses as a by-product, comparable to those calculated by other methods. We made the GAMA photo-z catalogue and all the codes and scripts used for the analysis and figures publicly available. 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. Future work will focus on incorporating additional photometric data and applying the TOPz algorithm to J-PAS narrow-band survey, further validating and enhancing its capabilities.