Photometric redshifts for the Pan-STARRS1 survey^⋆

¹ AIM, CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, 91191 Gif-sur-Yvette, France
² Observatorio Astronómico Nacional (OAN-IGN), C/ Alfonso XII 3, 28014 Madrid, Spain
e-mail: p.tarrio@oan.es

Received: 13 May 2020
Accepted: 28 July 2020

Abstract

We present a robust approach to estimating the redshift of galaxies using Pan-STARRS1 photometric data. Our approach is an application of the algorithm proposed for the SDSS Data Release 12. It uses a training set of 2 313 724 galaxies for which the spectroscopic redshift is obtained from SDSS, and magnitudes and colours are obtained from the Pan-STARRS1 Data Release 2 survey. The photometric redshift of a galaxy is then estimated by means of a local linear regression in a 5D magnitude and colour space. Our approach achieves an average bias of Δ̅z̅_n̅o̅r̅m̅ = −1.92 × 10⁻⁴, a standard deviation of σ(Δz_norm) = 0.0299, and an outlier rate of P_o = 4.30% when cross-validating the training set. Even though the relation between each of the Pan-STARRS1 colours and the spectroscopic redshifts is noisier than for SDSS colours, the results obtained by our approach are very close to those yielded by SDSS data. The proposed approach has the additional advantage of allowing the estimation of photometric redshifts on a larger portion of the sky (∼3/4 vs ∼1/3). The training set and the code implementing this approach are publicly available at the project website.