Photometric selection of Type Ia supernovae in the Supernova Legacy Survey

¹ CEA, Centre de Saclay, Irfu/SPP, 91191 Gif-sur-Yvette, France
² LPNHE, Université Pierre et Marie Curie, Université Paris Diderot, CNRS-IN2P3, 4 place Jussieu, 75252 Paris Cedex 05, France
³ University Paris 11, 91405 Orsay, France
⁴ LAM, CNRS-INSU, BP 8, Pôle de l’étoile, Site de Château-Gombert, 38 rue Frédéric Joliot-Curie, 13388 Marseille Cedex 13, France
⁵ Deparment of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H8, Canada
⁶ Center for Astrophysics and Space Astronomy, University of Colorado, Boulder, CO 80309-0389, USA
⁷ CPPM, CNRS-Luminy, Case 907, 13288 Marseille Cedex 9, France
⁸ Department of Physics (Astrophysics), University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, UK
⁹ INAF – Osservatorio Astronomico di Roma, via Frascati 33, 00040 Monteporzio ( RM), Italy
¹⁰ Las Cumbres Observatory Global Telescope Network, 6740 Cortona Dr., Suite 102, Goleta, CA 93117, USA
¹¹ Department of Physics, University of California, Santa Barbara, Broida Hall, Mail Code 9530, Santa Barbara, CA 93106-9530, USA
¹² Network Information Operations, DRDC-Ottawa, 3701 Carling Avenue, Ottawa, ON, K1A 0Z4, Canada
¹³ Department of Physics and Astronomy, University of Victoria, PO Box 3055, Victoria, BC V8W 3P6, Canada
¹⁴ Australian Astronomical Observatory, PO Box 296, Epping, NSW 1710, Australia
¹⁵ LBNL, 1 Cyclotron Rd, Berkeley, CA 94720, USA
¹⁶ Scuola Normale Superiore, Piazza des Cavalieri 7, 56126 Pisa, Italy
¹⁷ Department of Physics, Ludwig-Maximilians-Universität, Scheinerstr. 1, 81679 München and Excellence Cluster Universe, Boltzmannstr. 2, 85748 Garchhing, Germany

Received: 16 March 2011
Accepted: 23 August 2011

Abstract

We present a sample of 485 photometrically identified Type Ia supernova candidates mined from the first three years of data of the CFHT SuperNova Legacy Survey (SNLS). The images were submitted to a deferred processing independent of the SNLS real-time detection pipeline. Light curves of all transient events were reconstructed in the g_M, r_M, i_M and z_M filters and submitted to automated sequential cuts in order to identify possible supernovae. Pure noise and long-term variable events were rejected by light curve shape criteria. Type Ia supernova identification relied on event characteristics fitted to their light curves assuming the events to be normal SNe Ia. The light curve fitter SALT2 was used for this purpose, assigning host galaxy photometric redshifts to the tested events. The selected sample of 485 candidates is one magnitude deeper than that allowed by the SNLS spectroscopic identification. The contamination by supernovae of other types is estimated to be 4%. Testing Hubble diagram residuals with this enlarged sample allows us to measure the Malmquist bias due to spectroscopic selections directly. The result is fully consistent with the precise Monte Carlo based estimate used to correct SN Ia distance moduli in the SNLS 3-year cosmological analyses. This paper demonstrates the feasibility of a photometric selection of high redshift supernovae with known host galaxy redshifts, opening interesting prospects for cosmological analyses from future large photometric SN Ia surveys.