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Journal Articles Astronomy and Astrophysics - A&A Year : 2020

Photometric redshifts for the Pan-STARRS1 survey


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 Δ̅z̅n̅o̅r̅m̅ = −1.92 × 10−4, a standard deviation of σ(Δznorm) = 0.0299, and an outlier rate of Po = 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.
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cea-02965063 , version 1 (13-10-2020)



Paula Tarrío, Stefano Zarattini. Photometric redshifts for the Pan-STARRS1 survey. Astronomy and Astrophysics - A&A, 2020, 642, pp.A102. ⟨10.1051/0004-6361/202038415⟩. ⟨cea-02965063⟩
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