Statistics – Applications
Scientific paper
Dec 2003
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003aas...203.7819r&link_type=abstract
American Astronomical Society Meeting 203, #78.19; Bulletin of the American Astronomical Society, Vol. 35, p.1328
Statistics
Applications
Scientific paper
We present and analyze a catalog of ˜ 90,000 UV-excess quasar candidates to g=21 from the imaging data of the Sloan Digital Sky Survey (SDSS) First Data Release (DR1). Candidates were selected using a Kernel Density Estimation (KDE) algorithm that is up to 95% efficient in its selection of unresolved UVX quasars while maintaining over 80% completeness to confirmed DR1 quasars and providing for accurate photometric redshifts. We highlight possible science applications of such a large photometric sample of quasars and discuss future improvements, including incorporating magnitudes and pushing to higher redshifts and fainter quasars.
Brunner Robert J.
Gray Alexander G.
Lupton Robert H.
Nichol Robert C.
Richards Gordon T.
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