Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 372, Issue 2, Pages 565-577Publisher
WILEY-BLACKWELL
DOI: 10.1111/j.1365-2966.2006.10930.x
Keywords
methods : statistical; galaxies : distances and redshifts; galaxies : evolution; galaxies : formation; galaxies : photometry
Categories
Ask authors/readers for more resources
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 I-AB <= 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 5 sigma clipping that excludes <= 10 galaxies, both the Maximum Likelihood and Bayesian ZEBRA estimates for this sample have an accuracy sigma(Delta z)/( 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available