Overconfidence in Photometric Redshift Estimation

Abstract

We describe a new test of photometric redshift performance given a spectroscopic redshift sample. This test complements the traditional comparison of redshift {\it differences} by testing whether the probability density functions $p(z)$ have the correct {\it width}. We test two photometric redshift codes, BPZ and EAZY, on each of two data sets and find that BPZ is consistently overconfident (the $p(z)$ are too narrow) while EAZY produces approximately the correct level of confidence. We show that this is because EAZY models the uncertainty in its spectral energy distribution templates, and that post-hoc smoothing of the BPZ $p(z)$ provides a reasonable substitute for detailed modeling of template uncertainties. Either remedy still leaves a small surplus of galaxies with spectroscopic redshift very far from the peaks. Thus, better modeling of low-probability tails will be needed for high-precision work such as dark energy constraints with the Large Synoptic Survey Telescope and other large surveys.

arXiv commentaccepted to MNRAS

References in corpus (19)

• EAZY: A Fast, Public Photometric Redshift Code
• Bayesian photometric redshift estimation
• Galaxies in the Hubble Ultra Deep Field: I. Detection, Multiband Photometry, Photometric Redshifts, and Morphology
• A new catalog of photometric redshifts in the Hubble Deep Field
• A Critical Assessment of Photometric Redshift Methods: A CANDELS Investigation
• The PRIsm MUlti-Object Survey (PRIMUS) I: Survey Overview and Characteristics
• Calibrating Redshift Distributions Beyond Spectroscopic Limits with Cross-Correlations
• Effect of Photometric Redshift Uncertainties on Weak Lensing Tomography
• PHAT: PHoto-z Accuracy Testing
• The PRIsm MUlti-object Survey (PRIMUS). II. Data Reduction and Redshift Fitting
• First Results On Shear-Selected Clusters From the Deep Lens Survey: Optical Imaging, Spectroscopy, and X-ray Followup
• Precision photometric redshift calibration for galaxy-galaxy weak lensing
• A blind test of photometric redshift prediction
• The Deep Lens Survey
• A blind test of photometric redshifts on ground-based data
• Error analysis of the photometric redshift tecnique
• What Lies Beneath: Using p(z) to Reduce Systematic Photometric Redshift Errors
• Improved Photometric Redshifts via Enhanced Estimates of System Response, Galaxy Templates, and Magnitude Priors
• Photometric Redshifts and Photometry Errors

Cited by in corpus (33)

• Observational constraints on the merger history of galaxies since $z\approx 6$: Probabilistic galaxy pair counts in the CANDELS fields
• All-purpose, all-sky photometric redshifts for the Legacy Imaging Surveys Data Release 8
• Photometric redshifts for the next generation of deep radio continuum surveys - I: Template fitting
• The LOFAR Two-metre Sky Survey IV. First Data Release: Photometric redshifts and rest-frame magnitudes
• METAPHOR: A machine learning based method for the probability density estimation of photometric redshifts
• Photometric redshifts for the next generation of deep radio continuum surveys - II. Gaussian processes and hybrid estimates
• Morpho-z: improving photometric redshifts with galaxy morphology
• Improving Photometric Redshift Estimation using GPz: size information, post processing and improved photometry
• Cosmology with dropout selection: Straw-man surveys and CMB lensing
• The miniJPAS survey: the photometric redshift catalogue
• Data-driven, interpretable photometric redshifts trained on heterogeneous and unrepresentative data
• An ALMA survey of the SCUBA-2 Cosmology Legacy SurveyUKIDSS/UDS Field: Halo Masses for Submillimetre Galaxies
• Assessing the photometric redshift precision of the S-PLUS survey: the Stripe-82 as a test-case
• A Unified Framework for Constructing, Tuning and Assessing Photometric Redshift Density Estimates in a Selection Bias Setting
• Quantifying the suppression of the (un)-obscured star formation in galaxy cluster cores at 0.2$\lesssim$$z$$\lesssim$0.9
• Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies
• A Census of WISE-selected Dual and Offset AGN Across the Sky: New Constraints on Merger-Driven Triggering of Obscured AGN
• A Bayesian method for combining theoretical and simulated covariance matrices for large-scale structure surveys
• Photometric Redshift Estimation with Galaxy Morphology using Self-Organizing Maps
• TOPz: Photometric redshifts for J-PAS
• The LOFAR Two-metre Sky Survey Deep Fields -- Data Release 1: IV. Photometric redshifts and stellar masses
• pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model
• Identification of single spectral lines through supervised machine learning in a large HST survey (WISP): a pilot study for Euclid and WFIRST
• Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case
• Gaussian Mixture Models for Blended Photometric Redshifts
• Rejection criteria based on outliers in the KiDS photometric redshifts and PDF distributions derived by machine learning
• CLAP. I. Resolving miscalibration for deep learning-based galaxy photometric redshift estimation
• The miniJPAS survey: Maximising the photo-z accuracy from multi-survey datasets with probability conflation
• Characterising Improvements in Photometric Redshift Probability Density Functions with Galaxy Morphology
• The Impact of Tomographic Redshift Bin Width Errors on Cosmological Probes
• The Redshifts from 122 Bands: Comparative Redshift Forecast for Low-Resolution Spectra from SPHEREx and 7-Dimensional Sky Survey (7DS)
• CNN photometric redshifts in the SDSS at $r\le 20$
• TOPz: Photometric redshifts using template fitting applied to the GAMA survey