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Using AGN Variability Surveys to explore the AGN-Galaxy Connection

Published online by Cambridge University Press:  25 July 2014

Vicki L. Sarajedini*
Affiliation:
Department of Astronomy, University of Florida, 211 Bryant Space Science Center, Gainesville, FLUSA email: [email protected]
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Abstract

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Variability is a successful technique used to identify active galactic nuclei in both ground and space-based galaxy surveys. Optical variability surveys using HST have uncovered a number of AGN in deep extragalactic fields extending to z ~ 3 and probing intrinsically faint sources. Mid-IR variability surveys using Spitzer have identified a significant number of AGN and are particularly sensitive to obscured sources. Many variability-detected AGN are not strong X-ray sources or lack the characteristic colors of AGN and would thus be unidentified using other selection techniques. In this conference proceedings, I discuss the nature of the variable sources and their host galaxies identified in deep extragalactic optical and mid-IR surveys.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2014 

References

Ashby, M., et al. 2013, ApJ, 769, 80CrossRefGoogle Scholar
Bershady, M. A., Trevese, D., & Kron, R. G. 1998, ApJ, 505, 50CrossRefGoogle Scholar
Boutsia, K., Leibundgut, B., Trevese, D., & Vagnetti, F. 2009. A&A, 497, 81Google Scholar
Ferrarese, L. & Merritt, D. 2000, ApJL, 539, 9Google Scholar
Gebhardt, K., et al. 2000, ApJL, 539, 13Google Scholar
Giavalisco, et al. 2004, ApJL, 600, 93CrossRefGoogle Scholar
Glass, I. S. 2004, MNRAS, 350, 1049Google Scholar
Grogin, N. A., et al. 2005, ApJ, 627, 97Google Scholar
Grogin, N. A., et al. 2011, ApJS, 197, 35Google Scholar
Hickox, R. C., et al. 2009, ApJ, 696, 891Google Scholar
Honig, S. F. & Kishimoto, M. 2011, A&A, 534, 121Google Scholar
Hopkins, P. F., Bundy, K., Hernquist, L., & Ellis, R. S. 2007, ApJ, 659, 976Google Scholar
Kocevski, D. D.et al. 2012, ApJ, 744, 148Google Scholar
Kormendy, J. & Richstone, D. 1995, ARA&A, 33, 581Google Scholar
Li, S-L. & Cao, X. 2008, MNRAS, 387, 41Google Scholar
MacLeod, C. L., et al. 2010, ApJ, 721, 1014Google Scholar
Morokuma, T., et al. 2008, ApJ, 676, 121Google Scholar
Nandra, K.et al. 2007, ApJL, 660, 11Google Scholar
Perez-Gonzalez, P. G., Rieke, G. H. & Villar, V., et al. 2008, ApJ, 675, 234Google Scholar
Sarajedini, V. L., Koo, D. C., Klesman, A., Laird, E., Perez-Gonzalez, P. G., & Mozena, M. 2011, ApJ, 731, 97CrossRefGoogle Scholar
Sarajedini, V. L., Gilliland, R. L., & Kasm, C. 2003, ApJ, 599, 173CrossRefGoogle Scholar
Schmidt, K. B., Marshall, P. J., Rix, H-W., Jester, S., Hennawi, J. F., & Dobler, G. 2010, ApJ, 714, 1194CrossRefGoogle Scholar
Trevese, D., Kron, R. G., Majewski, S. R., & Koo, D. C. 1994, ApJ, 433, 494CrossRefGoogle Scholar
Trevese, D., Boutsia, K., Vagnetti, F., Cappellaro, E., & Puccetti, S. 2008, A&A, 488, 73Google Scholar
Villforth, C., Sarajedini, V., & Koekemoer, A. 2012, MNRAS, 426, 360Google Scholar
Wilhite, B. C., Brunner, R. J., Grier, C. J., Schneider, D. P. & Vanden Berk, D. E. 2008, MNRAS, 283, 1232Google Scholar
Williams, R. E., et al. 1996, AJ, 112, 1335Google Scholar
Zuo, W., Wu, X-B., Liu, Y-Q., & Jiao, C-L. 2012, ApJ, 758, 104Google Scholar