Abstract
We present the first comprehensive release of photometric redshifts (photo- z's) from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) team. We use statistics based upon the Quantile-Quantile (Q-Q) plot to identify biases and signatures of underestimated or overestimated errors in photo- z probability density functions (PDFs) produced by six groups in the collaboration; correcting for these effects makes the resulting PDFs better match the statistical definition of a PDF. After correcting each group’s PDF, we explore three methods of combining the different groups’ PDFs for a given object into a consensus curve. Two of these methods are based on identifying the minimum f-divergence curve, i.e., the PDF that is closest in aggregate to the other PDFs in a set (analogous to the median of an array of numbers). We demonstrate that these techniques yield improved results using sets of spectroscopic redshifts independent of those used to optimize PDF modifications. The best photo- z PDFs and point estimates are achieved with the minimum f-divergence using the best four PDFs for each object (mFDa4) and the hierarchical Bayesian (HB4) methods, respectively. The HB4 photo- z point estimates produced σ NMAD = 0.0227/0.0189 and ∣Δz/(1 + z)∣ > 0.15 outlier fraction = 0.067/0.019 for spectroscopic and 3D Hubble Space Telescope redshifts, respectively. Finally, we describe the structure and provide guidance for the use of the CANDELS photo- z catalogs, which are available at https://archive.stsci.edu/prepds/candels/.
| Original language | English (US) |
|---|---|
| Article number | 36 |
| Journal | Astrophysical Journal |
| Volume | 942 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2023 |
Bibliographical note
Funding Information:We would like to thank Janine Pforr for performing the HyperZ fits. We also wish to acknowledge helpful discussions with Larry Wasserman, Ann Lee, Peter Freeman, and the International Computational Astrostatistics Group at Carnegie Mellon University; Rongpu Zhou; members of the CANDELS Multiwavelength Catalog Working Group and the LSST Dark Energy Science Collaboration Photometric Redshift Working Group. We appreciate the careful reading and thoughtful suggestions by the referee and the AAS Journals statistician. This work is based on observations taken by the CANDELS Multi-Cycle Treasury Program with the NASA/ESA HST and was supported by HST program No. GO-12060. Support for Program No. GO-12060 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. D.C.K. acknowledges support from NSF grant AST-1615730. This research has made use of NASA’s Astrophysics Data System.
Funding Information:
We would like to thank Janine Pforr for performing the HyperZ fits. We also wish to acknowledge helpful discussions with Larry Wasserman, Ann Lee, Peter Freeman, and the International Computational Astrostatistics Group at Carnegie Mellon University; Rongpu Zhou; members of the CANDELS Multiwavelength Catalog Working Group and the LSST Dark Energy Science Collaboration Photometric Redshift Working Group. We appreciate the careful reading and thoughtful suggestions by the referee and the AAS Journals statistician. This work is based on observations taken by the CANDELS Multi-Cycle Treasury Program with the NASA/ESA HST and was supported by HST program No. GO-12060. Support for Program No. GO-12060 was provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. D.C.K. acknowledges support from NSF grant AST-1615730. This research has made use of NASA’s Astrophysics Data System.
Publisher Copyright:
© 2023. The Author(s). Published by the American Astronomical Society.