EAZY: A Fast, Public Photometric Redshift Code
Gabriel B. Brammer, Pieter G. van Dokkum, Paolo Coppi

TL;DR
EAZY is a fast, flexible photometric redshift code that uses semi-analytical models for templates, providing reliable redshift estimates without relying on spectroscopic training data.
Contribution
It introduces a novel template error function and a redshift quality parameter, improving accuracy and reliability of photometric redshifts without spectroscopic training.
Findings
Achieves a 1-sigma scatter of 0.034 in dz/(1+z) on deep field datasets.
Performs well on public datasets without spectroscopic training.
Provides updated photometric redshift catalogs for major surveys.
Abstract
We describe a new program for determining photometric redshifts, dubbed EAZY. The program is optimized for cases where spectroscopic redshifts are not available, or only available for a biased subset of the galaxies. The code combines features from various existing codes: it can fit linear combinations of templates, it includes optional flux- and redshift-based priors, and its user interface is modeled on the popular HYPERZ code. A novel feature is that the default template set, as well as the default functional forms of the priors, are not based on (usually highly biased) spectroscopic samples, but on semi-analytical models. Furthermore, template mismatch is addressed by a novel rest-frame template error function. This function gives different wavelength regions different weights, and ensures that the formal redshift uncertainties are realistic. We introduce a redshift quality…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Galaxies: Formation, Evolution, Phenomena
