Optical identifications and spectroscopy of a faint radio source sample: the nature of the sub-mJy population

Astronomy and Astrophysics – Astrophysics

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15 pages, 10 figs, accepted for publication in MNRAS

Scientific paper

10.1046/j.1365-8711.1999.02301.x

Deep imaging and spectroscopy have been carried out for optical counterparts of a sample of 68 faint radio sources (S > 0.2 mJy) in the ``Marano Field''. About 60% of the sources have been optically identified on deep CCD exposures (limit R ~ 24.0) or ESO 3.6-m plates (limit bJ ~ 22.5). Thirty-four spectra (50% of the total radio sample) were obtained with the ESO 3.6-m telescope and 30 redshifts were determined. In addition to a few broad line active galactic nuclei, three main spectroscopic classes have been found to dominate the faint radio galaxy population: (1) Early-type galaxies with 0.1 < z < 0.8. (2) Late-type galaxies at moderate redshift (z < 0.4), with relatively bright magnitudes (B < 22.5) and sub-mJy radio fluxes. (3) A group of bright high-redshift (z > 0.8) radio galaxies with moderate-to-strong [OII] emission. They have spectra, colours and absolute magnitudes similar to those of the classical bright elliptical radio galaxies found in surveys carried out at higher radio fluxes. Star-forming galaxies do not constitute the main population of our radio sources identified with galaxies. In fact, even at sub-mJy level the majority of our radio sources are identified with early-type galaxies. This apparent discrepancy with previous results is due to the fainter magnitude limit reached in our spectroscopic identifications. Moreover, using mainly the large radio-to-optical ratio and the information from the available limits on the optical magnitudes of the unidentified radio sources, we conclude that the great majority of them are likely to be early-type galaxies, at z > 1. If correct, it would suggest that the evolution of the radio luminosity function of spiral galaxies, including starbursts, might not be as strong as suggested in previous evolutionary models.

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