Kavli Affiliate: Rafe Schindler
| First 5 Authors: Julia Gschwend, Aurelio Carnero Rosell, Ricardo Ogando, Angelo Fausti Neto, Marcio Maia
| Summary:
A significant challenge facing photometric surveys for cosmological purposes
is the need to produce reliable redshift estimates. The estimation of
photometric redshifts (photo-zs) has been consolidated as the standard strategy
to bypass the high production costs and incompleteness of spectroscopic
redshift samples. Training-based photo-z methods require the preparation of a
high-quality list of spectroscopic redshifts, which needs to be constantly
updated. The photo-z training, validation, and estimation must be performed in
a consistent and reproducible way in order to accomplish the scientific
requirements. To meet this purpose, we developed an integrated web-based data
interface that not only provides the framework to carry out the above steps in
a systematic way, enabling the ease testing and comparison of different
algorithms, but also addresses the processing requirements by parallelizing the
calculation in a transparent way for the user. This framework called the
Science Portal (hereafter Portal) was developed in the context the Dark Energy
Survey (DES) to facilitate scientific analysis. In this paper, we show how the
Portal can provide a reliable environment to access vast data sets, provide
validation algorithms and metrics, even in the case of multiple photo-zs
methods. It is possible to maintain the provenance between the steps of a chain
of workflows while ensuring reproducibility of the results. We illustrate how
the Portal can be used to provide photo-z estimates using the DES first year
(Y1A1) data. While the DES collaboration is still developing techniques to
obtain more precise photo-zs, having a structured framework like the one
presented here is critical for the systematic vetting of DES algorithmic
improvements and the consistent production of photo-zs in the future DES
releases.
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