Herschel-ATLAS : VISTA VIKING near-infrared counterparts in the Phase 1 GAMA 9-h data
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Author
Fleuren, S.
Sutherland, W.
Dunne, L.
Smith, Daniel
Maddox, S. J.
Gonzalez-Nuevo, J.
Findlay, J.
Auld, R.
Baes, M.
Bond, N. A.
Bonfield, D. G.
Bourne, N.
Cooray, A.
Buttiglione, S.
Cava, A.
Dariush, A.
De Zotti, G.
Driver, S. P.
Dye, S.
Eales, S.
Fritz, J.
Gunawardhana, M. L. P.
Hopwood, R.
Ibar, E.
Ivison, R. J.
Jarvis, M.J.
Kelvin, L.
Lapi, A.
Liske, J.
Michalowski, M. J.
Negrello, M.
Pascale, E.
Pohlen, M.
Prescott, M.
Rigby, E. E.
Robotham, A.
Scott, D.
Temi, P.
Thompson, Mark
Valiante, E.
van der Werf, P.
Attention
2299/8778
Abstract
We identify near-infrared Ks-band counterparts to Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) submillimetre (submm) sources, using a preliminary object catalogue from the VISTA Kilo-degree Infrared Galaxy (VIKING) survey. The submm sources are selected from the H-ATLAS Phase 1 catalogue of the Galaxy and Mass Assembly 9-h field, which includes all objects detected at 250, 350 or with the instrument. We apply and discuss a likelihood ratio method for VIKING candidates within a search radius of 10 arcsec of the 22 000 SPIRE sources with a 5s detection at . We estimate the fraction of SPIRE sources with a counterpart above the magnitude limit of the VIKING survey to be Q0 similar to 0.73. We find that 11 294 (51 per cent) of the SPIRE sources have a best VIKING counterpart with a reliability R= 0.8, and the false identification rate of these is estimated to be 4.2 per cent. We expect to miss 5 per cent of true VIKING counterparts. There is evidence from Z-J and J-Ks colours that the reliable counterparts to SPIRE galaxies are marginally redder than the field population. We obtain photometric redshifts for 68 per cent of all (non-stellar) VIKING candidates with a median redshift of . We have spectroscopic redshifts for 3147 (28 per cent) of the reliable counterparts from existing redshift surveys. Comparing to the results of the optical identifications supplied with the Phase 1 catalogue, we find that the use of medium-deep near-infrared data improves the identification rate of reliable counterparts from 36 to 51 per cent.