Statistics – Computation
Scientific paper
Jan 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aas...21714263c&link_type=abstract
American Astronomical Society, AAS Meeting #217, #142.63; Bulletin of the American Astronomical Society, Vol. 43, 2011
Statistics
Computation
Scientific paper
With upcoming surveys such as LSST poised to generate a deep movie of the optical/UV sky, variability-based selection promises to generate highly-complete AGN catalogs while minimizing contamination. To prepare for large time-domain surveys, photometric analyses are currently focusing on SDSS Stripe 82 because it covers a large area of sky (about 300 square degrees) with 70 epochs of observations in each of five (ugriz) filters. We are exploring an alternate approach to variability-based selection in Stripe 82 data, using difference-imaging code developed for the LSST survey. Difference imaging analyses do not need to assume or fit a source model, so they excel at identifying variable sources embedded in complex or blended emission regions. Our initial goal in this project is to identify AGN that are surrounded by host-galaxy emission, including lower-luminosity AGN that may be omitted from photometric or spectroscopic catalogs. We describe algorithmic and computational challenges faced by such an analysis and compare our results to existing catalogs of Stripe 82 sources in order to determine the best strategies for distinguishing AGN from star-forming galaxies, quiescent galaxies, and other types of sources that can contaminate AGN catalogs.
Becker Andrew
Choi Yumi
Connolly Andrew J.
Gibson Robert R.
Ivezic Zeljko
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