Mining the SDSS archive. I. Photometric redshifts in the nearby universe

Details Mining the SDSS archive. I. Photometric redshifts in the nearby universe Mining the SDSS archive. I. Photometric redshifts in the nearby universe

2007-03-06

arxiv.org/abs/astro-ph/0703108v2

Astrophys.J.663:752-764,2007

Astronomy and Astrophysics

Astrophysics

45 pages, 14 figures, accepted for publication is the Astrophysical Journal

Scientific paper

10.1086/518020

We present a supervised neural network approach to the determination of photometric redshifts. The method was tuned to match the characteristics of the Sloan Digital Sky Survey and it exploits the spectroscopic redshifts provided by this unique survey. In order to train, validate and test the networks we used two galaxy samples drawn from the SDSS spectroscopic dataset: the general galaxy sample (GG) and the luminous red galaxies subsample (LRG). The method consists of a two steps approach. In the first step, objects are classified in nearby (z<0.25) and distant (0.25

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