Spectroscopy of luminous z>7 galaxy candidates and sources of contamination in z>7 galaxy searches

Astronomy and Astrophysics – Astrophysics – Cosmology and Extragalactic Astrophysics

Scientific paper

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15 Pages, 15 figures, accepted to ApJ

Scientific paper

10.1088/0004-637X/730/2/68

We present three bright z+ dropout candidates selected from deep Near-Infrared (NIR) imaging of the COSMOS 2 square degree field. All three objects match the 0.8-8um colors of other published z>7 candidates but are three magnitudes brighter, facilitating further study. Deep spectroscopy of two of the candidates covering 0.64-1.02um with Keck-DEIMOS and all three covering 0.94-1.10um and 1.52-1.80um with Keck-NIRSPEC detects weak spectral features tentatively identified as Ly-alpha at z=6.95 and z=7.69 in two of the objects. The third object is placed at z~1.6 based on a 24um and weak optical detection. A comparison with the spectral energy distributions of known z<7 galaxies, including objects with strong spectral lines, large extinction, and large systematic uncertainties in the photometry yields no objects with similar colors. However, the lambda>1um properties of all three objects can be matched to optically detected sources with photometric redshifts at z~1.8, so the non-detection in the i+ and z+ bands are the primary factors which favors a z>7 solution. If any of these objects are at z~7 the bright end of the luminosity function is significantly higher at z>7 than suggested by previous studies, but consistent within the statistical uncertainty and the dark matter halo distribution. If these objects are at low redshift, the Lyman-Break selection must be contaminated by a previously unknown population of low redshift objects with very strong breaks in their broad band spectral energy distributions and blue NIR colors. The implications of this result on luminosity function evolution at high redshift is discussed. We show that the primary limitation of z>7 galaxy searches with broad filters is the depth of the available optical data.

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