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The Hubble Space Telescope GOODS NICMOS Survey: Overview and the Evolution of Massive Galaxies at 1.5 < z < 3

We present the details and early results from a deep near-infrared survey utilising the NICMOS instrument on the Hubble Space Telescope centred around massive M_* > 10^11 M_0 galaxies at 1.7 < z < 2.9 found within the Great Observatories Origins Deep Survey (GOODS) fields. The GOODS NICMOS Survey (GNS) was designed to obtain deep F160W (H-band) imaging of 80 of these massive galaxies, as well as other colour selected objects such as Lyman-break drop-outs, BzK objects, Distant Red Galaxies, EROs, Spitzer Selected EROs, BX/BM galaxies, as well as sub-mm galaxies. We present in this paper details of the observations, our sample selection, as well as a description of features of the massive galaxies found within our survey fields. This includes: photometric redshifts, rest-frame colours, and stellar masses. We furthermore provide an analysis of the selection methods for finding massive galaxies at high redshifts, including colour selection, and how galaxy populations selected through different methods overlap. We find that a single colour selection method cannot locate all of the massive galaxies, with no one method finding more than 70 percent. We however find that the combination of these colour methods finds nearly all the massive galaxies, as selected by photometric redshifts with the exception of apparently rare blue massive galaxies. By investigating the rest-frame (U-B) vs. M_B diagram for these galaxies we furthermore show that there exists a bimodality in colour-magnitude space at z < 2, driven by stellar mass, such that the most massive galaxies are systematically red up to z~2.5, while lower mass galaxies tend to be blue. We also discuss the number densities for galaxies with stellar masses M_* > 10^11 M_0, whereby we find an increase of a factor of eight between z = 3 and z = 1.5, demonstrating that this is an epoch when massive galaxies establish most of their mass.

preprint2010arXivOpen access

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