EAZY: A Fast, Public Photometric Redshift Code

By G. Brammer, P. V. van Dokkum, Paolo De Coppi. 2008

1,434 citations recorded by the source corpus.

We describe a new program for determining photometric redshifts, dubbed EAZY. The program is optimized for cases where spectroscopic redshifts are not available, or are 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 semianalytical 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 parameter, Qz, which provides a robust estimate of the reliability of the photometric redshift estimate. Despite the fact that EAZY is not ”trained” on spectroscopic samples, the code (with default parameters) performs very well on existing public data sets. For K-selected samples in CDF-South and other deep fields, we find a 1 σ scatter in Δ z/(1 + z) of 0.034, and we provide updated photometric redshift catalogs for the FIRES, MUSYC, and FIREWORKS surveys.

Subfields: Astronomy and Astrophysics, Instrumentation, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/156d19bbf5e5c88554cfa20cfc06e6e8bef3e70c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Astronomy and Astrophysics

1. P. Hopkins
2. L. Hernquist
3. R. Dav'e
4. P. V. van Dokkum
5. C. Conroy
6. R. Somerville
7. M. Franx
8. A. Dekel

In Instrumentation

1. P. V. van Dokkum
2. P. Hopkins
3. C. Conroy
4. L. Hernquist
5. M. Franx
6. R. Dav'e
7. A. Dekel
8. R. Somerville

In Statistical and Nonlinear Physics

1. C. Conroy
2. P. V. van Dokkum
3. Risa Wechsler
4. M. Franx
5. M. Kriek
6. A. Dekel
7. P. Behroozi
8. I. Labbé

Citations in the corpus

• SIZES AND SURFACE BRIGHTNESS PROFILES OF QUIESCENT GALAXIES AT z ∼ 2 (2011, methodology): “This catalog combines observations of the Chandra Deep Field South ranging from ground-basedU-band data toSpitzer 24 µm data, and includes spectroscopic redshifts where available, as well as photometric redshifts derived using EAZY (Brammer et al. 2008).”
• CEERS Epoch 1 NIRCam Imaging: Reduction Methods and Simulations Enabling Early JWST Science Results (2022, background): “…Collaboration et al. 2013), Besançon Model of the Galaxy (doi:10.25666/ osu-theta.20210107.galaxy-model), Drizzle (Fruchter & Hook 2002), EAZY (Brammer et al. 2008), Mirage (mirage-data-simulator.readthedocs.io), Photutils (Bradley et al. 2020), SciPy (Virtanen et al. 2020), Source Extractor…”
• THE NEWFIRM MEDIUM-BAND SURVEY: PHOTOMETRIC CATALOGS, REDSHIFTS, AND THE BIMODAL COLOR DISTRIBUTION OF GALAXIES OUT TO z ∼ 3 (2011, methodology): “Photometric redshifts and rest-frame colors were derived using the EAZY code25 (Brammer et al. 2008), that fits linear combinations of seven templates to the broad- and medium-band SEDs.”
• PROBING THE DAWN OF GALAXIES AT z ∼ 9–12: NEW CONSTRAINTS FROM HUDF12/XDF AND CANDELS DATA (2013, methodology): “While Ellis et al. (2013) find a bestfit photometric redshift of 8.6 ± 0.7, the source is not present in the ‘robust’ sample of McLure et al. (2012), and we find a photometric redshift distribution function which is very broad, with a best-fit at z ∼ 0.5 (using both ZEBRA or EAZY).”
• TWO MICRON ALL SKY SURVEY PHOTOMETRIC REDSHIFT CATALOG: A COMPREHENSIVE THREE-DIMENSIONAL CENSUS OF THE WHOLE SKY (2013, methodology): “Note that we have chosen to use the term ’outliers’, without identifying them as ’catastrophic’, as the latter are ambiguously defined in the literature (see e.g. Ilbert et al. 2006; Brammer et al. 2008; Oyaizu et al. 2008; Brescia et al. 2013 for different variants).”
• GOODS-HERSCHEL: STAR FORMATION, DUST ATTENUATION, AND THE FIR–RADIO CORRELATION ON THE MAIN SEQUENCE OF STAR-FORMING GALAXIES UP TO z ≃ 4 (2014, methodology): “Photometric redshifts Photometric redshifts were estimated by runningEAZY1 (Brammer et al. 2008) on the multi-wavelength catalog.”
• THE EVOLUTION OF THE GALAXY STELLAR MASS FUNCTION AT z = 4–8: A STEEPENING LOW-MASS-END SLOPE WITH INCREASING REDSHIFT (2015, methodology): “Photometric redshifts were estimated with EAZY (Brammer et al. 2008), and selection criteria devised based on the full redshift probability density function (pdf; P (z)) were applied (Finkelstein et al. 2015).”
• KECK SPECTROSCOPY OF FAINT 3 < z < 8 LYMAN BREAK GALAXIES: EVIDENCE FOR A DECLINING FRACTION OF EMISSION LINE SOURCES IN THE REDSHIFT RANGE 6 < z < 8 (2011, methodology): “For each target, we determine its redshift probability function p(z) using the photometric redshift code EAZY (Brammer et al. 2008).”
• ON THE STELLAR POPULATIONS AND EVOLUTION OF STAR-FORMING GALAXIES AT 6.3 < z ⩽ 8.6 (2009, methodology): “We find that differences in stellar libraries and IGM treatment between our fitting method and that of EAZY result in a slightly higher redshift from this fitting, by a few tenths on average, with a range in the sample from 6.50≤ z ≤ 8.85.”
• Modelling and interpreting spectral energy distributions of galaxies with BEAGLE (2016, methodology): “MNRAS 462, 1415–1443 (2016) by guest on O ctober 5, 2016 http://m nras.oxfordjournals.org/ D ow nloaded from zBPZ − zspec 0.005 0.028 2.4 per cent zEAZY − zspec −0.013 0.030 5.9 per cent zBEAGLE − zspec 0.007 0.047 7.1 per cent zBEAGLE − zBPZ 0.005 0.042 8.3 per cent zBEAGLE − zEAZY 0.039 0.058 7.3 ”
• THE RELATION BETWEEN STAR FORMATION RATE AND STELLAR MASS FOR GALAXIES AT 3.5 ⩽ z ⩽ 6.5 IN CANDELS (2014, background): “The σMAD is an analog for the 68% confidence, σ, if the error distribution were Gaussian and is therefore less sensitive to outliers (see Brammer et al. 2008).”
• CONSTRAINING THE LOW-MASS SLOPE OF THE STAR FORMATION SEQUENCE AT 0.5 < z < 2.5 (2014, methodology): “To determine the grism redshifts, we first compute a purely photometric redshift from the photometry, using the EAZY code (Brammer et al. 2008).”
• THE MULTIWAVELENGTH SURVEY BY YALE–CHILE (MUSYC): DEEP MEDIUM-BAND OPTICAL IMAGING AND HIGH-QUALITY 32-BAND PHOTOMETRIC REDSHIFTS IN THE ECDF-S (2010, methodology): “…we use the median 68% confidence intervals computed by EAzY to compare the quality of the photometric redshifts for all 21 ∆z=|zspec − zphot| 22 We calculate the normalized median absolute deviation (NMAD) as σNMAD = 1.48×median ∣ ∣ ∣ ∣ ∆z−median(∆z) 1 + zspec ∣ ∣ ∣ ∣ as in (Brammer et al. 2008).”
• Identification of the brightest Lyα emitters at z = 6.6 : Implications for the evolution of the luminosity function in the reionization era (2015, background): “1 (Brammer et al. 2008), which includes the contribution of emission lines (although typically not strong enough for the observed extreme emission lines galaxies).”
• A PUBLIC Ks-SELECTED CATALOG IN THE COSMOS/UltraVISTA FIELD: PHOTOMETRY, PHOTOMETRIC REDSHIFTS, AND STELLAR POPULATION PARAMETERS, (2013, methodology): “EAZY also accounts for potential mismatches between the data and the templates via the “template error function” (see Brammer et al. 2008).”
• A POPULATION OF MASSIVE, LUMINOUS GALAXIES HOSTING HEAVILY DUST-OBSCURED GAMMA-RAY BURSTS: IMPLICATIONS FOR THE USE OF GRBs AS TRACERS OF COSMIC STAR FORMATION (2013, methodology): “Nevertheless, the redshift can be constrained by our broadband data; the 95% confidence redshift range from EaZy is 1.98 < z < 3.08 with a best-fit value of 2.47.”
• ON STAR FORMATION RATES AND STAR FORMATION HISTORIES OF GALAXIES OUT TO z ∼ 3 (2011, methodology): “For the remaining sources, we derived highquality photometric redshifts using EAZY (Brammer et al. 2008).”