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Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks
- Source :
- Astronomy & Astrophysics, 616, A69, A&A, 616, 1, Astronomy & astrophysics, 616(August 2018):A69. EDP Sciences, Astronomy & Astrophysics
- Publication Year :
- 2018
-
Abstract
- We present a machine-learning photometric redshift analysis of the Kilo-Degree Survey Data Release 3, using two neural-network based techniques: ANNz2 and MLPQNA. Despite limited coverage of spectroscopic training sets, these ML codes provide photo-zs of quality comparable to, if not better than, those from the BPZ code, at least up to zphot<br />A&A, in press. Data available from the KiDS website http://kids.strw.leidenuniv.nl/DR3/ml-photoz.php#annz2
- Subjects :
- Cosmology and Nongalactic Astrophysics (astro-ph.CO)
Infrared
astro-ph.GA
galaxies: distances and redshifts, catalogs, large-scale structure of Universe, methods: data analysis, methods: numerical, methods: statistical
FOS: Physical sciences
Phot
Astrophysics
01 natural sciences
methods: numerical
Photometry (optics)
0103 physical sciences
010303 astronomy & astrophysics
Instrumentation and Methods for Astrophysics (astro-ph.IM)
Photometric redshift
Physics
methods: statistical
010308 nuclear & particles physics
Sigma
Astronomy and Astrophysics
methods: data analysis
Astrophysics - Astrophysics of Galaxies
Redshift
Galaxy
Space and Planetary Science
Astrophysics of Galaxies (astro-ph.GA)
astro-ph.CO
large-scale structure of Universe
galaxies: distances and redshifts
Astrophysics - Instrumentation and Methods for Astrophysics
Order of magnitude
catalogs
astro-ph.IM
Astrophysics - Cosmology and Nongalactic Astrophysics
Subjects
Details
- Language :
- English
- ISSN :
- 00046361 and 1406345X
- Volume :
- 616
- Database :
- OpenAIRE
- Journal :
- Astronomy & astrophysics
- Accession number :
- edsair.doi.dedup.....71f1bae3a9d0aa8ed8db020d08b5aeb4