Improved Photometric Redshifts with Surface Luminosity Priors
Abstract
We apply Bayesian statistics with prior probabilities of galaxy surface luminosity (SL) to improve photometric redshifts. We apply the method to a sample of 1266 galaxies with spectroscopic redshifts in the GOODS North and South fields at 0.1 < z < 2.0. We start with spectrophotometric redshifts (SPZs) based on Probing Evolution and Reionization Spectroscopically grism spectra, which cover a wavelength range of 6000-9000A, combined with (U)BViz(JHK) broadband photometry in the GOODS fields. The accuracy of SPZ redshifts is estimated to be \sigma (\Delta(z))=0.035 with an systematic offset of -0.026, where \Delta(z)=\Delta z / (1+z), for galaxies in redshift range of 0.5 < z < 1.25. The addition of the SL prior probability helps break the degeneracy of SPZ redshifts between low redshift 4000 A break galaxies and high-redshift Lyman break galaxies which are mostly catastrophic outliers. For the 1138 galaxies at z < 1.6, the fraction of galaxies with redshift deviation \Delta (z) > 0.2 is reduced from 15.0% to 10.4%, while the rms scatter of the fractional redshift error does not change much.
Cite
@article{arxiv.0906.0985,
title = {Improved Photometric Redshifts with Surface Luminosity Priors},
author = {Lifang Xia and Seth Cohen and Sangeeta Malhotra and James Rhoads and Norman Grogin and Nimish P. Hathi and Rogier A. Windhorst and Nor Pirzkal and Chun Xu},
journal= {arXiv preprint arXiv:0906.0985},
year = {2015}
}
Comments
7 pages, 7 figures, published in AJ