Astronomy and Astrophysics – Astrophysics
Scientific paper
2005-03-03
Astronomy and Astrophysics
Astrophysics
ApJ Suppl, in press. Figures converted to JPEG/GIF for better compression; PDF with full-resolution figures available before p
Scientific paper
10.1086/430050
We present 180 AGN candidates based on color selection from the IRAS slow-scan deep observations, with color criteria broadened from the initial Point-Source Catalog samples to include similar objects with redshifts up to z=1 and allowing for two-band detections. Spectroscopic identifications have been obtained for 80 (44%); some additional ones are secure based on radio detections or optical morphology, although yet unobserved spectroscopically. These spectroscopic identifications include 13 Sy 1 galaxies, 17 Sy 2 Seyferts, 29 starbursts, 7 LINER systems, and 13 emission-line galaxies so heavily reddened as to remain of ambiguous classification. The optical magnitudes range from R=12.0-20.5; counts suggest that incompleteness is important fainter than R=15.5. Redshifts extend to z=0.51, with a significant part of the sample at z>0.2. The sample includes slightly more AGN than star-forming systems among those where the spectra contain enough diagnostic feature to make the distinction. The active nuclei include several broad-line objects with strong Fe II emission, and composite objects with the absorption-line signatures of fading starbursts. These AGN with warm far-IR colors have little overlap with the "red AGN" identified with 2MASS; only a single Sy 1 was detected by 2MASS with J-K > 2. Some reliable IRAS detections have either very faint optical counterparts or only absorption-line galaxies, potentially being deeply obscured AGN. The IRAS detections include a newly identified symbiotic star, and several possible examples of the "Vega phenomenon", including dwarfs as cool as type K. Appendices detail these candidate stars, and the optical-identification content of a particularly deep set of high-latitude IRAS scans (probing the limits of optical identification from IRAS data alone).
de Grijp Marinus H. K.
Gallimore Jack F.
Golombek Daniel
Irby Bryan K.
Keel William C.
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