T. Dahlen, B. Mobasher, S. M. Faber, H. C. Ferguson, G. Barro, S. L. Finkelstein, K. Finlator, A. Fontana, R. GrŁtzbauch, S. Johnson, J. Pforr, M. Salvato, T. Wiklind, S. Wuyts, V. Acquaviva, M. E. Dickinson, Y. Guo, J. Huang, K. H. Huang, J. A. Newman, E. F. Bell, C. J. Conselice, A. Galametz, E. Gawiser, M. Giavalisco, N. A. Grogin, N. P. Hathi, D. Kocevski, A. M. Koekemoer, D. C. Koo, K. S. Lee, E. J. McGrath, C. Papovich, M. Peth, R. Ryan, R. Somerville, B. Weiner, G. Wilson
We present results from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey(CANDELS) photometric redshift methods investigation. In this investigation, the results from 11 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 broadband 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 that 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.
galaxies: distances: and: redshifts - galaxies: high-redshift - galaxies: photometry - surveys
The Astrophysical Journal
Volume 775, Number 2, Page 93_1