A census of object types and redshift estimates in the SDSS photometric catalog from a trained decision tree classifier

作者：Suchkov AA^*; Hanisch RJ; Margon B

来源：Astronomical Journal, 2005, 130(6): 2439-2452.

DOI：10.1086/497363

• astronomical data bases : miscellaneous
• galaxies : active
• galaxies : distances and redshifts
• quasars : general

We have applied ClassX, an oblique decision tree classifier optimized for astronomical analysis, to the homogeneous multicolor imaging database of the Sloan Digital Sky Survey (SDSS), training the software on subsets of SDSS objects whose nature is precisely known via spectroscopy. We find that the software, using photometric data only, correctly classifies a very large fraction of the objects with existing SDSS spectra, both stellar and extragalactic. ClassX also accurately predicts the redshifts of both normal and active galaxies in SDSS. To illustrate ClassX applications in SDSS research, we (1) derive the object content of the SDSS Data Release 2 photometric catalog and (2) provide a sample catalog of resolved SDSS objects that contains a large number of candidate active galactic nucleus (AGN) galaxies (27,000), along with 63,000 candidate normal galaxies at magnitudes substantially fainter than the typical magnitudes of SDSS spectroscopic objects. The surface density of AGNs selected by ClassX to i similar to 19 is in agreement with that quoted by SDSS. When ClassX is applied to photometric data fainter than the SDSS spectroscopic limit, the inferred surface density of AGNs rises sharply, as expected. The ability of the classifier to accurately constrain the redshifts of huge numbers (ultimately similar to 10(7)) of active galaxies in the photometric database promises new insights into fundamental issues of AGN research, such as the evolution of the AGN luminosity function with cosmic time, the starburst-AGN connection, and AGN-galactic morphology relationships.

• 出版日期2005-12