Principal Component Analysis of New QSO Samples

Details Principal Component Analysis of New QSO Samples Principal Component Analysis of New QSO Samples

Dec 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003aas...203.7824h&link_type=abstract

American Astronomical Society Meeting 203, #78.24; Bulletin of the American Astronomical Society, Vol. 35, p.1329

Astronomy and Astrophysics

Astronomy

1

Scientific paper

The underlying goal of studies of the phenomenology of AGN characteristics is to relate correlations among properties to physical processes and their parameters. Principal component analysis (PCA) is a statistical tool that has been used with great success to determine correlations among AGN properties, but an understanding of the physical processes responsible for the relationships discovered using PCA (most notably that set of relationships known as Eigenvector 1) has yet to be achieved. The SDSS, with its large size, uniform quality and well-defined selection criteria, promises to be a valuable part of understanding these relationships. A preliminary analysis of 120 EDR quasars and 80 DR1 quasars reveals that the Eigenvector 1 trends are strongly present in SDSS quasars and that [OII] and [OIII] luminosities are correlated with the Eigenvector 1 properties. Those objects emitting near their Eddington limits, with [OIII] too broad for their black hole mass, display blue asymmetries on their [OIII] lines. Principal component analysis of all 200 SDSS quasars combined with the sample of PG quasars was also conducted, revealing strong, well-defined Eigenvector 1 trends.
Hughes's research was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation through Scientific Program Order No. 3 (AST-0243875) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF.

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