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Title:
Improved Photometric Redshifts with Surface Brightness Priors
Authors:
Xia, Lifang; Cohen, S.; Malhotra, S.; Rhoads, J.; Grogin, N.; Hathi, N.; Pirzkal, N.; Xu, C.; Pears Team
Affiliation:
AA(Arizona State University), AB(Arizona State University), AC(Arizona State University), AD(Arizona State University), AE(Arizona State University), AF(Arizona State University), AG(Space Telescope Science Institute), AH(Space Telescope Science Institute), AI()
Publication:
American Astronomical Society, AAS Meeting #211, #132.21; Bulletin of the American Astronomical Society, Vol. 39, p.965
Publication Date:
12/2007
Origin:
AAS
Bibliographic Code:
2007AAS...21113221X

Abstract

We apply Bayesian statistics and prior probabilities of galaxy surface brightness to improve photometric redshift estimation. We first estimate the spectro-photometric redshifts (SPZs) for all 1873 galaxies for which we have ground-based spectroscopic redshifts. The spectro-photometric redshifts are based on the grism spectra, which cover a wavelength range of 6000-9000 Angstroms, combined with (U)BViz(JHK) broad-band photometry in the GOODS fields (Cohen et al. 2007, Ryan et al. 2007). The addition of the prior probability of surface brightness reduces redshift uncertainties by a factor of two to three. It also reduces the number of catastrophic outliers. Finally, we apply the improved redshift estimator to the full PEARS sample.
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arXiv e-prints