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We measure photometric redshifts and spectral types for galaxies in the COSMOS survey. We use template fitting technique combined with luminosity function priors and with the option to simultaneously estimate dust extinction (i.e. E(B-V)) for each galaxy.Our estimated redshifts are accurate to i<25 and z~1.2. Using simulations with sampling and noise characteristics similar to those in COSMOS, the accuracy and reliability is estimated for the photometric redshifts as a function of the magnitude limits of the sample, S/N ratios and the number of bands used. From the simulations we find that the ratio of derived 95% confidence interval in the redshift probability distribution to the estimated photometric redshift (D95) can be used to identify and exclude the catastrophic failures in the photometric redshift estimates. We compare the derived redshifts with high-reliability spectroscopic redshifts for a sample of 868 normal galaxies with z < 1.2 from zCOSMOS. Considering different scenarios, depending on using prior, no prior and/or extinction, we compare the photometric and spectroscopic redshifts for this sample. This corresponds to an rms scatter of 0.031, with a small number of outliers (<2.5%). We also find good agreement (rms=0.10) between photometric and spectroscopic redshifts for Type II AGNs. We compare results from our photometric redshift procedure with three other independent codes and find them in excellent agreement. We show preliminary results, based on photometric redshifts for the entire COSMOS sample (to i < 25 mag.).
We present accurate photometric redshifts in the 2-deg2 COSMOS field. The redshifts are computed with 30 broad, intermediate, and narrow bands covering the UV (GALEX), Visible-NIR (Subaru, CFHT, UKIRT and NOAO) and mid-IR (Spitzer/IRAC). A chi2 templ
We use extensive multi-wavelength photometric data from the Great Observatories Origins Deep Survey (GOODS) to estimate photometric redshifts for a sample of 434 galaxies with spectroscopic redshifts in the Chandra Deep Field South. Using the Bayesia
We apply clustering-based redshift inference to all extended sources from the Sloan Digital Sky Survey photometric catalogue, down to magnitude r = 22. We map the relationships between colours and redshift, without assumption of the sources spectral
In this work I discuss the necessary steps for deriving photometric redshifts for luminous red galaxies (LRGs) and galaxy clusters through simple empirical methods. The data used is from the Sloan Digital Sky Survey (SDSS). I show that with three ban
Upcoming imaging surveys, such as LSST, will provide an unprecedented view of the Universe, but with limited resolution along the line-of-sight. Common ways to increase resolution in the third dimension, and reduce misclassifications, include observi