Photometric Redshift Error Estimators

Citations Over TimeTop 10% of 2008 papers

Abstract

Photometric redshift (photo-z) estimates are playing an increasingly important role in extragalactic astronomy and cosmology. Crucial to many photo-z applications is the accurate quantification of photometric redshift errors and their distributions, including identification of likely catastrophic failures in photo-z estimates. We consider several methods of estimating photo-z errors and propose new training-set based error estimators based on spectroscopic training set data. Using data from the Sloan Digital Sky Survey and simulations of the Dark Energy Survey as examples, we show that this method provides a robust, relatively unbiased estimate of photo-z errors. We show that culling objects with large, accurately estimated photo-z errors from a sample can reduce the incidence of catastrophic photo-z failures.

Related Papers

• → Constraining dark energy with Hubble parameter measurements: an analysis including future redshift-drift observations(2016)66 cited
• → WHAT LIES BENEATH: USING p ( z ) TO REDUCE SYSTEMATIC PHOTOMETRIC REDSHIFT ERRORS(2009)44 cited
• → Calibrating photometric redshifts of luminous red galaxies(2005)105 cited
• → Constraints on the Physical Parameters of the Dark Energy Using a Model-Independent Approach(2005)3 cited
• → Calibrating Photometric Redshifts of Luminous Red Galaxies(2004)