Photometric redshifts for the Kilo-Degree Survey - Machine-learning analysis with artificial neural networks

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Volume 616 (August 2018)

A&A, 616 (2018) A69

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Table 1.

Spectroscopic samples constituting the KiDS DR3 photo-z training set.

Sample	Number of sources^a	Mean z^a	Mean r mag^a	Reference(s)
GAMA-II equatorial	190 741	0.234	19.5	Liske et al. (2015)
SDSS DR13 galaxies	56 911	0.349	19.6	Albareti et al. (2017)
GAMA G23	38 854	0.238	19.3	proprietary
zCOSMOS^b	25 888	0.813	22.2	private comm. & Davies et al. (2015)
2dFLenS	11 873	0.362	19.6	Blake et al. (2016)
DEEP2 DR4 (two fields)	8924	0.962	23.5	Newman et al. (2013)
CDFS^c	7044	0.846	22.9	online & Cooper et al. (2012)
GAMA G15-deep	2286	0.340	21.1	proprietary
Total^d	312 501	0.335	19.9
Total cleaned^e	278 946	0.332	19.9

Notes.

^(a)

After cross-match with KiDS DR3, without masking nor quality cuts in KiDS.

^(b)

Data from zCOSMOS public and non-public catalogues, as well as from the GAMA-G10 catalogue.

^(c)

Data from GOODS/CDF-S compilation and from ACES.

^(d)

Duplicate entries removed.

^(e)

After cleaning of bad photometry as described in Sect. 3.5.

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