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26 April 2024 |
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A Critical Assessment of Photometric Redshift Methods: A CANDELS Investigation | | Tomas Dahlen
; Bahram Mobasher
; Sandra M. Faber
; Henry C. Ferguson
; Guillermo Barro
; Steven L. Finkelstein
; Kristian Finlator
; Adriano Fontana
; Ruth Gruetzbauch
; Seth Johnson
; Janine Pforr
; Mara Salvato
; Tommy Wiklind
; Stijn Wuyts
; Viviana Acquaviva
; Mark E. Dickinson
; Yicheng Guo
; Jiasheng Huang
; Kuang-Han Huang
; Jeffrey A. Newman
; Eric F. Bell
; Christopher J. Conselice
; Audrey Galametz
; Eric Gawiser
; Mauro Giavalisco
; Norman A. Grogin
; Nimish Hathi
; Dale Kocevski
; Anton M. Koekemoer
; David C. Koo
; Kyoung-Soo Lee
; Elizabeth J. McGrath
; Casey Papovich
; Michael Peth
; Russell Ryan
; Rachel Somerville
; Benjamin Weiner
; Grant Wilson
; | | Date: |
24 Aug 2013 | | Abstract: | We present results from the Cosmic Assembly Near-infrared Deep Extragalactic
Legacy Survey (CANDELS) photometric redshift methods investigation. In this
investigation, the results from eleven participants, each using a different
combination of photometric redshift code, template spectral energy
distributions (SEDs) and priors, are used to examine the properties of
photometric redshifts applied to deep fields with broad-band multi-wavelength
coverage. The photometry used includes U-band through mid-infrared filters and
was derived using the TFIT method. Comparing the results, we find that there is
no particular code or set of template SEDs that results in significantly better
photometric redshifts compared to others. However, we find codes producing the
lowest scatter and outlier fraction utilize a training sample to optimize
photometric redshifts by adding zero-point offsets, template adjusting or
adding extra smoothing errors. These results therefore stress the importance of
the training procedure. We find a strong dependence of the photometric redshift
accuracy on the signal-to-noise ratio of the photometry. On the other hand, we
find a weak dependence of the photometric redshift scatter with redshift and
galaxy color. We find that most photometric redshift codes quote redshift
errors (e.g., 68% confidence intervals) that are too small compared to that
expected from the spectroscopic control sample. We find that all codes show a
statistically significant bias in the photometric redshifts. However, the bias
is in all cases smaller than the scatter, the latter therefore dominates the
errors. Finally, we find that combining results from multiple codes
significantly decreases the photometric redshift scatter and outlier fraction.
We discuss different ways of combining data to produce accurate photometric
redshifts and error estimates. | | Source: | arXiv, 1308.5353 | | Services: | Forum | Review | PDF | Favorites | |
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