9-D Bayesian Quasar Classification in the Mid-IR/Optical

Details 9-D Bayesian Quasar Classification in the Mid-IR/Optical 9-D Bayesian Quasar Classification in the Mid-IR/Optical

May 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006sptz.prop30347r&link_type=abstract

Spitzer Proposal ID #30347

Astronomy and Astrophysics

Astronomy

Scientific paper

One of the hottest topics in extragalactic astronomy is the identification and census of type 2 quasars. Type 2 selection benefits enormously from the high quality imaging data afforded by the Spitzer Space Telescope since these objects are generally too obscured in the optical for efficient selection in that bandpass. We propose to develop a novel classification algorithm to aid in this endeavor. Bayesian quasar classification based on Kernel Density Estimation (Richards et al. 2004) and photometric redshift estimation (Weinstein et al. 2004) has already been shown to be very efficient in the optical using only the 5 SDSS bandpasses. Additional bandpasses, such as afforded by Spitzer-IRAC imaging, can be used to further improve this selection method and photometric redshift estimation. With appropriate tuning of our algorithms, we can meet two key goals. First is to construct a catalog of type 1 quasars in the roughly 50 square degrees of sky that currently have (or will have by the end of 2006), public data from both SDSS and Spitzer-IRAC. Such a catalog (including accurate photometric redshifts) will enable a second goal, namely more efficient type 2 quasar searches. We will improve the efficiency of type 2 quasar discovery by removing those mid-IR luminous type 1 quasars from the sample of objects that are currently being followed-up with multi-object spectroscopy on larger telescopes, and also by better isolating the type 2 quasar parameter space. We request 49927 of support to adapt our classification and photometric redshift algorithms to make use of the Spitzer-IRAC data and to publish a catalog of quasars identified by these algorithms.

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