From Sloan Digital Sky Survey (SDSS) commissioning photometric and spectroscopic data, we investigate the utility of photometric redshift techniques in the task of estimating QSO redshifts. We consider empirical methods (e.g., nearest neighbor searches and polynomial fitting), standard spectral template fitting, and hybrid approaches (i.e., training spectral templates from spectroscopic and photometric observations of QSOs). We find that in all cases, because of the presence of strong emission lines within the QSO spectra, the nearest neighbor and template-fitting methods are superior to the polynomial- fitting approach. Applying a novel reconstruction technique, we can, from the SDSS multicolor photometry, reconstruct a statistical representation of the underlying SEDs of the SDSS QSOs. Although the reconstructed templates are based on only broadband photometry, the common emission lines present within the QSO spectra can be recovered in the resulting spectral energy distributions. The technique should be useful in searching for spectral differences among QSOs at a given redshift, in searching for spectral evolution of QSOs, in comparing photometric redshifts for objects beyond the SDSS spectroscopic sample with those in the well-calibrated photometric redshifts for objects brighter than 20th magnitude, and in searching for systematic and time-variable effects in the SDSS broadband photometric and spectral photometric calibrations.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science