arXiv · astro-ph/0407594
Calibrating Photometric Redshifts of Luminous Red Galaxies
Abstract
We discuss the construction of a photometric redshift catalogue of Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS), emphasizing the principal steps necessary for constructing such a catalogue -- (i) photometrically selecting the sample, (ii) measuring photometric redshifts and their error distributions, (iii) and estimating the true redshift distribution. We compare two photometric redshift algorithms for these data and find that they give comparable results. Calibrating against the SDSS and SDSS-2dF spectroscopic surveys, we find that the photometric redshift accuracy is $σ\sim 0.03$ for redshifts less than 0.55 and worsens at higher redshift ($\sim 0.06$). These errors are caused by photometric scatter, as well as systematic errors in the templates, filter curves, and photometric zeropoints. We also parametrize the photometric redshift error distribution with a sum of Gaussians, and use this model to deconvolve the errors from the measured photometric redshift distribution to estimate the true redshift distribution. We pay special attention to the stability of this deconvolution, regularizing the method with a prior on the smoothness of the true redshift distribution. The methods we develop are applicable to general photometric redshift surveys.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Nikhil Padmanabhan, Tamas Budavari, David J. Schlegel, Terry Bridges, Jonathan Brinkmann, Russell Cannon, Andrew J. Connolly, Scott M. Croom, Istvan Csabai, Michael Drinkwater, Daniel J. Eisenstein, Paul C. Hewett, Jon Loveday, Robert C. Nichol, Kevin A. Pimbblet, Roberto De Propris, Donald P. Schneider, Ryan Scranton, Uros Seljak, Tom Shanks, Istvan Szapudi, Alexander S. Szalay, David Wake. 2005-05-24. Calibrating Photometric Redshifts of Luminous Red Galaxies. https://doi.org/10.1111/j.1365-2966.2005.08915.x%2Fabs%2F
Cite the original work for its findings. Save a collection to share your selection of sources.