Photometric Redshifts for Galaxies in the GOODS Southern Field
Author(s) -
Bahram Mobasher,
R. Idzi,
N. Bentez,
A. Cimatti,
S. Cristiani,
E. Daddi,
T. Dahlén,
Mark Dickinson,
T. Erben,
Henry C. Ferguson,
Mauro Giavalisco,
Norman A. Grogin,
Anton M. Koekemoer,
M. Mignoli,
Leonidas A. Moustakas,
M. ino,
P. Rosati,
M. Schirmer,
Daniel Stern,
E. Vanzella,
Christian Wolf,
G. Zamorani
Publication year - 2004
Publication title -
the astrophysical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.376
H-Index - 489
eISSN - 1538-4357
pISSN - 0004-637X
DOI - 10.1086/378186
Subject(s) - redshift , astrophysics , physics , galaxy , photometric redshift , outlier , astronomy , artificial intelligence , computer science
We use extensive multi-wavelength photometric data from the GreatObservatories Origins Deep Survey (GOODS) to estimate photometric redshifts fora sample of 434 galaxies with spectroscopic redshifts in the Chandra Deep FieldSouth. Using the Bayesian method, which incorporates redshift/magnitude priors,we estimate photometric redshifts for galaxies in the range 18 < R (AB) < 25.5,giving an rms scatter of 0.11. The outlier fraction is < 10%, with theoutlier-clipped rms being 0.047. We examine the accuracy of photometricredshifts for several, special sub--classes of objects. The results forextremely red objects are more accurate than those for the sample as a whole,with rms of 0.051 and very few outliers (3%). Photometric redshifts for activegalaxies, identified from their X-ray emission, have a dispersion of 0.104,with 10% outlier fraction, similar to that for normal galaxies. Employing aredshift/magnitude prior in this process seems to be crucial in improving theagreement between photometric and spectroscopic redshifts.
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