Accurate photometric redshifts for the CFHT legacy survey calibrated using the VIMOS VLT deep survey
Università di Bologna, Dipartimento di Astronomia, via Ranzani 1, 40127, Bologna, Italy e-mail: email@example.com
2 Laboratoire d'Astrophysique de Marseille, UMR 6110 CNRS-Université de Provence, BP 8, 13376 Marseille Cedex 12, France
3 Institut d'Astrophysique de Paris, UMR7095 CNRS, Université Pierre & Marie Curie, 98bis boulevard Arago, 75014 Paris, France
4 Observatoire de Paris, LERMA, 61 avenue de l'Observatoire, 75014 Paris, France
5 INAF-Osservatorio Astronomico di Bologna, via Ranzani 1, 40127, Bologna, Italy
6 Laboratoire d'Astrophysique de l'Observatoire Midi-Pyrénées, UMR 5572, 14 avenue E. Belin, 31400 Toulouse, France
7 INAF-Osservatorio Astronomico di Brera, via Brera 28, Milan, Italy
8 IASF-INAF – via Bassini 15, 20133, Milano, Italy
9 INAF-Osservatorio Astronomico di Roma, via di Frascati 33, 00040, Monte Porzio Catone, Italy
10 IRA-INAF – via Gobetti,101, 40129, Bologna, Italy
11 School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
12 European Southern Observatory, Garching, Germany
13 Centre de Physique Théorique, Marseille, France
14 Integral Science Data Centre, Ch. d'Écogia 16, 1290 Versoix, Switzerland
15 Geneva Observatory, Ch. des Maillettes 51, 1290 Sauverny, Switzerland
16 INAF-Osservatorio Astronomico di Capodimonte, via Moiariello 16, 80131, Napoli, Italy
Accepted: 8 July 2006
Aims. We present and release photometric redshifts for a uniquely large and deep sample of 522286 objects with in the Canada-France Hawaii Telescope Legacy Survey (CFHTLS) “Deep Survey” fields D1, D2, D3, and D4, which cover a total effective area of 3.2 .
Methods. We use 3241 spectroscopic redshifts with from the VIMOS VLT Deep Survey (VVDS) as a calibration and training set to derive these photometric redshifts. Using the “Le Phare” photometric redshift code, we developed a robust calibration method based on an iterative zero-point refinement combined with a template optimisation procedure and the application of a Bayesian approach. This method removes systematic trends in the photometric redshifts and significantly reduces the fraction of catastrophic errors (by a factor of 2), a significant improvement over traditional methods. We use our unique spectroscopic sample to present a detailed assessment of the robustness of the photometric redshift sample.
Results. For a sample selected at , we reach a redshift accuracy of with of catastrophic errors (η is defined strictly as those objects with ). The reliability of our photometric redshifts decreases for faint objects: we find and for samples selected at –22.5 and 22.5–24 respectively. We find that the photometric redshifts of starburst galaxies are less reliable: although these galaxies represent only 22% of the spectroscopic sample, they are responsible for 50% of the catastrophic errors. An analysis as a function of redshift demonstrates that our photometric redshifts work best in the redshift range . We find an excellent agreement between the photometric and the VVDS spectroscopic redshift distributions at . Finally, we compare the redshift distributions of i' selected galaxies on the four CFHTLS deep fields, showing that cosmic variance is still present on fields of 0.7–0.9 deg2. These photometric redshifts are made publicly available at http://terapix.iap.fr (complete ascii catalogues) and http://cencos.oamp.fr/cencos/CFHTLS/ (searchable database interface).
Key words: galaxies: distances and redshifts / galaxies: photometry / methods: data analysis
© ESO, 2006