We present the Zurich Extragalactic Bayesian Redshift Analyzer (ZEBRA). The current version of ZEBRA combines and extends several of the classical approaches to produce accurate photometric redshifts down to faint magnitudes. In particular, ZEBRA uses the template-fitting approach to produce Maximum Likelihood and Bayesian redshift estimates based on the following points. (i) An automatic iterative technique to correct the original set of galaxy templates to best represent the Spectral Energy Distributions (SEDs) of real galaxies at different redshifts. (ii) A training set of spectroscopic redshifts for a small fraction of the photometric sample to improve the robustness of the photometric redshift estimates. (iii) An iterative technique for Bayesian redshift estimates, which extracts the full two-dimensional redshift and template probability function for each galaxy. We demonstrate the performance of ZEBRA by applying it to a sample of 866 IAB ≤ 22.5 COSMOS galaxies with available u*, B, V, g′, r′, i′, z′ and K s photometry and zCOSMOS spectroscopic redshifts in the range 0 < z < 1.3. Adopting a 5σ clipping that excludes ≤10 galaxies, both the Maximum Likelihood and Bayesian ZEBRA estimates for this sample have an accuracy σΔz/(1+z) smaller than 0.03. Similar accuracies are recovered using mock galaxies. ZEBRA is made available at http://www.exp-astro.phys.ethz.ch/ZEBRA.
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