Study of ultraviolet-optical properties of a complete sample of QSOs

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Date

2003

Authors

Shang, Zhaohui

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Abstract

Spectral principal component analysis (SPCA) has been applied to a complete sample of 22 low-redshift QSOs with spectral data of broad wavelength coverage from Lyα to Hα. QSO spectra are decomposed into three significant, independent principal components — line-core, continuum slope, and line-width. The line-core component represents the Baldwin effect, but only emission line cores, or emissions from low-velocity gas, are correlated with the continuum luminosity. The scatter in this luminosity relationship is greatly reduced, rekindling the hope of using QSOs as “standard candles” in cosmological studies. The continuum slope component shows the QSO intrinsic continuum slope possibly reshaped by the dust reddening. The line-width component expands the Boroson and Green’s Eigenvector 1 relationship to include many more UV and optical spectral properties. This principal component is suggested to be driven by the Eddington accretion rate. The emission lines and continua of the spectra have also been directly measured. The correlation analyses and the principal component analysis on the measured parameters confirm the results from SPCA. The consistent results from the different analyses show conclusively that the Baldwin effect and the Boroson and Green’s Eigenvector 1 are two significant, independent relationships among QSO UV-optical spectral properties. There is also evidence from the direct correlation analyses that the low ionization lines are closely related with each other in terms of their FWHMs and velocity shifts, and it is similar for the high ionization UV lines, but no strong correlation is seen between the low and high ionization lines. This suggests that the structure of the broad line region is stratified in both ionization and velocity field, as also suggested by reverberation mapping studies. It is also demonstrated that SPCA is powerful and efficient in analyzing QSO spectra, especially for large samples.

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