J/A+A/651/A55 Predicted redshifts of galaxies with NetZ (Schuldt+, 2021)
Photometric Redshift estimation with a Convolutional Neural Network: NetZ.
Schuldt S., Suyu S.H., Canameras R., Taubenberger S., Meinhard T.,
Leal-Taixe L., Hsieh B.C.
<Astron. Astrophys. 651, A55 (2021)>
=2021A&A...651A..55S 2021A&A...651A..55S (SIMBAD/NED BibCode)
ADC_Keywords: Models ; Galaxies ; Redshifts
Keywords: catalogs - techniques: photometric - galaxies: photometry -
galaxies: high-redshift galaxies: distances and redshifts
Abstract:
The redshifts of galaxies are a key attribute that is needed for
nearly all extragalactic studies. Since spectroscopic redshifts
require additional telescope and human resources, millions of galaxies
are known without spectroscopic redshifts. Therefore, it is crucial to
have methods for estimating the redshift of a galaxy based on its
photometric properties, the so-called photo-z. We developed NetZ, a
new method using a Convolutional Neural Network (CNN) to predict the
photo-z based on galaxy images, in contrast to previous methods which
often used only the integrated photometries of galaxies without their
images. We use data from the Hyper Suprime-Cam Subaru Strategic
Program (HSC SSP) in five different filters as training data. The
network over the whole redshift range between 0 and 4 performs well
overall and especially in the high-z range better than other methods
on the same data. We obtain an accuracy |zpred-zref| of sigma=0.12
(68% confidence interval) with a CNN working for all galaxy types
averaged over all galaxies in the redshift range of 0 to ∼4. By
limiting to smaller redshift ranges or to Luminous Red Galaxies
(LRGs), we find a further notable improvement. We publish more than 34
million new photo-z values predicted with NetZ here. This shows that
the new method is very simple and fast to apply, and, importantly,
covers a wide redshift range limited only by the available training
data. It is broadly applicable and beneficial to imaging surveys,
particularly upcoming surveys like the Rubin Observatory Legacy Survey
of Space and Time which will provide images of billions of galaxies
with similar image quality as HSC.
Description:
We present a catalog of photometric redshifts predicted with our newly
developed code NetZ. The catalog contains 34414686 redshift entries
for galaxies from the HSC survey.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
catalog.dat 48 34414686 Catalog of photometric redshifts predicted with
our newly developed code NetZ
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Byte-by-byte Description of file: catalog.dat
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Bytes Format Units Label Explanations
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1- 17 I17 --- ID Galaxy identification number from the HSC PDR2
19- 28 F10.6 --- zpred ?=-99 photometric redshift estimated from
NetZ (1)
30- 38 F9.5 deg RAdeg Right Ascension (J2000)
40- 48 F9.5 deg DEdeg Declination in (J2000)
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Note (1): Galaxies with zpred<0 or zpred>5 flagged with zpred=-99.
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Acknowledgements:
Stefan Schuldt, stefan.schuldt(at)tum.de
(End) Patricia Vannier [CDS] 29-Apr-2021