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Spitzer's Contribution to the AGN Population

Using large multiwavelength datasets, we study obscured AGN in the distant universe that have been missed via traditional selection techniques (e.g. UV/ optical/X-ray). To do so, we take particular advantage of the mid-IR, which is minimally affected by obscuration. We first select as AGN candidates those objects whose radio emission is significantly brighter, relative to the mid-IR, than would be predicted by the well known radio/infrared correlation, indicating that the radio emission originates in the central engine. We find that of the 27 such sources identified in the CDF-N, 60% lack solid X-ray detections and 25% lack even 2σ X-ray emission. The absorbing columns of the faint X-ray–detected objects indicate that they are obscured but unlikely to be Compton thick, whereas the radio-excess AGN which are X-ray non-detected are Compton-thick candidates. We similarly use the infrared emission to select IRAC (3.6-8.0 μm) power-law AGN. In these luminous AGN, the hot dust emission from the AGN fills in the gap in a galaxy’s SED between the 1.6 μm stellar bump and the long-wavelength dust emission feature. While sources selected in this way are more luminous than the radio-excess AGN, we find a similar X-ray detection fraction. Of the 62 power-law galaxies in the CDF-N, only 55% are detected in the X-ray, and 15% lack evidence for even weak 2σ X-ray emission. A study of their X-ray properties indicates that ∼ 75% are obscured. Finally, we test IRAC color-color and infrared-excess selection criteria. We find that while these selection techniques identify a number of obscured AGN, they may also select a significant number of star-forming galaxies. By combining only the secure AGN candidates selected via all methods discussed above, we estimate that the addition of Spitzer-selected AGN candidates to the deepest Xray selected AGN samples directly increases the number of known AGN by 54- 77%, and implies a total increase to the number of AGN of 71-94%.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/195679
Date January 2009
CreatorsDonley, Jennifer Lynn
ContributorsRieke, George, Rieke, George, Shirley, Yancy, Dickinson, Mark, Impey, Chris, Green, Richard
PublisherThe University of Arizona.
Source SetsUniversity of Arizona
LanguageEnglish
Detected LanguageEnglish
Typetext, Electronic Dissertation
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.

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