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http://hdl.handle.net/20.500.12386/27595
Titolo: | Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks | Autori: | Bilicki, M. Hoekstra, H. Brown, M. J. I. Amaro, V. Blake, C. CAVUOTI, STEFANO de Jong, J. T. A. Georgiou, C. Hildebrandt, H. Wolf, C. Amon, A. BRESCIA, Massimo Brough, S. Costa-Duarte, M. V. Erben, T. Glazebrook, K. GRADO, ANIELLO Heymans, C. Jarrett, T. Joudaki, S. Kuijken, K. Longo, G. NAPOLITANO, NICOLA ROSARIO Parkinson, D. Vellucci, C. Verdoes Kleijn, G. A. Wang, L. |
Data pubblicazione: | 2018 | Rivista: | ASTRONOMY & ASTROPHYSICS | Numero: | 616 | Da pagina:: | A69 | Abstract: | We present a machine-learning photometric redshift (ML photo-z) analysis of the Kilo-Degree Survey Data Release 3 (KiDS DR3), 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 Bayesian Photometric Redshift (BPZ) code, at least up to z<SUB>phot</SUB> ≲ 0.9 and r ≲ 23.5. At the bright end of r ≲ 20, where very complete spectroscopic data overlapping with KiDS are available, the performance of the ML photo-zs clearly surpasses that of BPZ, currently the primary photo-z method for KiDS. Using the Galaxy And Mass Assembly (GAMA) spectroscopic survey as calibration, we furthermore study how photo-zs improve for bright sources when photometric parameters additional to magnitudes are included in the photo-z derivation, as well as when VIKING and WISE infrared (IR) bands are added. While the fiducial four-band ugri setup gives a photo-z bias <δz/(1 + z)> = -2 × 10<SUP>-4</SUP> and scatter σ<SUB>δz/(1+z)</SUB> < 0.022 at mean <z> = 0.23, combining magnitudes, colours, and galaxy sizes reduces the scatter by 7% and the bias by an order of magnitude. Once the ugri and IR magnitudes are joined into 12-band photometry spanning up to 12 μm, the scatter decreases by more than 10% over the fiducial case. Finally, using the 12 bands together with optical colours and linear sizes gives <δz/(1 + z)> < 4 × 10<SUP>-5</SUP> and σ<SUB>δz/(1+z)</SUB> < 0.019. This paper also serves as a reference for two public photo-z catalogues accompanying KiDS DR3, both obtained using the ANNz2 code. The first one, of general purpose, includes all the 39 million KiDS sources with four-band ugri measurements in DR3. The second dataset, optimised for low-redshift studies such as galaxy-galaxy lensing, is limited to r ≲ 20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation. | URI: | http://hdl.handle.net/20.500.12386/27595 | URL: | http://arxiv.org/abs/1709.04205v2 https://www.aanda.org/articles/aa/abs/2018/08/aa31942-17/aa31942-17.html |
ISSN: | 0004-6361 | DOI: | 10.1051/0004-6361/201731942 | Bibcode ADS: | 2018A&A...616A..69B | Fulltext: | open |
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