Photometric Redshift Error Estimators

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.

10 pages, 11 figures, submitted to ApJ

References in corpus (5)

• The Sixth Data Release of the Sloan Digital Sky Survey
• Estimating the Redshift Distribution of Faint Galaxy Samples
• A Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6
• Photometric Redshifts for the Dark Energy Survey and VISTA and Implications for Large Scale Structure
• Photometric Redshift Requirements for Self-Calibration of Cluster Dark Energy Studies

Cited by in corpus (48)

• An Empirical Characterization of Extended Cool Gas Around Galaxies Using MgII Absorption Features
• TPZ : Photometric redshift PDFs and ancillary information by using prediction trees and random forests
• The Blanco Cosmology Survey: Data Acquisition, Processing, Calibration, Quality Diagnostics and Data Release
• 2MASS Photometric Redshift catalog: a comprehensive three-dimensional census of the whole sky
• ANNz2 - photometric redshift and probability distribution function estimation using machine learning
• Supernova Simulations and Strategies For the Dark Energy Survey
• Photometric redshift analysis in the Dark Energy Survey Science Verification data
• Results from the Supernova Photometric Classification Challenge
• Constraining the Scatter in the Mass-Richness Relation of maxBCG Clusters With Weak Lensing and X-ray Data
• Redshift distributions of galaxies in the DES Science Verification shear catalogue and implications for weak lensing
• Estimating the Redshift Distribution of Photometric Galaxy Samples II. Applications and Tests of a New Method
• Cross-correlation Weak Lensing of SDSS Galaxy Clusters I: Measurements
• A statistical standard siren measurement of the Hubble constant from the LIGO/Virgo gravitational wave compact object merger GW190814 and Dark Energy Survey galaxies
• Catastrophic photometric redshift errors: weak lensing survey requirements
• UV-to-FIR analysis of Spitzer/IRAC sources in the Extended Groth Strip II: Photometric redshifts, Stellar masses and Star formation rates
• Measurements of the Rate of Type Ia Supernovae at Redshift z < ~0.3 from the SDSS-II Supernova Survey
• Spectroscopic Needs for Imaging Dark Energy Experiments: Photometric Redshift Training and Calibration
• Evaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST)
• Weak lensing, dark matter and dark energy
• The Galaxy Major Merger Fraction to z ~ 1
• The Clustering of MgII Absorption Systems at z=0.5 and Detection of Cold Gas in Massive Halos
• Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks
• Mass and galaxy distributions of four massive galaxy clusters from Dark Energy Survey Science Verification data
• A General Study of the Influence of Catastrophic Photometric Redshift Errors on Cosmology with Cosmic Shear Tomography
• The SDSS Coadd: Cosmic Shear Measurement
• Exhausting the Information: Novel Bayesian Combination of Photometric Redshift PDFs
• Morpho-z: improving photometric redshifts with galaxy morphology
• A Measurement of the Rate of Type Ia Supernovae in Galaxy Clusters from the SDSS-II Supernova Survey
• Sample variance in photometric redshift calibration: cosmological biases and survey requirements
• Bayesian photometric redshifts with empirical training sets
• Cosmology with the cluster mass function: mass estimators and shape systematics in large weak lensing surveys
• The SDSS Coadd: A Galaxy Photometric Redshift Catalog
• Spectroscopic failures in photometric redshift calibration: cosmological biases and survey requirements
• Robust determination of the major merger fraction at z = 0.6 in Groth Strip
• The miniJPAS survey: the photometric redshift catalogue
• I. Apples to apples $A^2$: realistic galaxy simulated catalogs and photometric redshift predictions for next-generation surveys
• Photometric redshifts with machine learning, lights and shadows on a complex data science use case
• Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies
• The ALHAMBRA survey : $B-$band luminosity function of quiescent and star-forming galaxies at $0.2\le z<1$ by PDF analysis
• The properties of Brightest Cluster Galaxies in the SDSS DR6 adaptive matched filter cluster catalogue
• SXDF-ALMA 2 Arcmin^2 Deep Survey: Resolving and Characterizing the Infrared Extragalactic Background Light Down to 0.5 mJy
• Automated measurement of redshift from mid-infrared low resolution spectroscopy
• Dark Matter Distribution of Four Low-z Clusters of Galaxies
• Degradation analysis in the estimation of photometric redshifts from non-representative training sets
• Reconstructing galaxy fundamental distributions and scaling relations from photometric redshift surveys. Applications to the SDSS early-type sample
• Probing the bias of radio sources at high redshift
• The environment of QSO triplets at 1 $\lesssim$ z $\lesssim$ 1.5
• The Limits of Photometric Dynamics: Benchmarking Cluster Relaxation Diagnostics