Accurate photometric redshifts for the CFHT legacy survey calibrated using the VIMOS VLT deep survey

¹ Università di Bologna, Dipartimento di Astronomia, via Ranzani 1, 40127, Bologna, Italy e-mail: ilbert@ifa.hawaii.edu
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

Received: 3 March 2006
Accepted: 8 July 2006

Abstract

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).