Quasar classification using color and variability

We conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys. We use a Bayesian quasar selection algorithm to identify 35,820 type 1 quasar candidates in a 239 deg{sup 2} field of the...

Full description

Saved in:
Bibliographic Details
Published in:The Astrophysical journal 2015-10, Vol.811 (2)
Main Authors: Peters, Christina M., Richards, Gordon T., Myers, Adam D., Strauss, Michael A., Schmidt, Kasper B., Ivezic, Željko, Ross, Nicholas P., MacLeod, Chelsea L., Riegel, Ryan
Format: Article
Language:English
Subjects:
ASTROPHYSICS, COSMOLOGY AND ASTRONOMY
CLASSIFICATION
COMPARATIVE EVALUATIONS
CURRENTS
LUMINOSITY
PHOTOMETRY
QUASARS
SPECTRA
STARS
STRUCTURE FUNCTIONS
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We conduct a pilot investigation to determine the optimal combination of color and variability information to identify quasars in current and future multi-epoch optical surveys. We use a Bayesian quasar selection algorithm to identify 35,820 type 1 quasar candidates in a 239 deg{sup 2} field of the Sloan Digital Sky Survey (SDSS) Stripe 82, using a combination of optical photometry and variability. Color analysis is performed on 5-band single- and multi-epoch SDSS optical photometry to a depth of r∼22.4. From these data, variability parameters are calculated by fitting the structure function of each object in each band with a power-law model using 10 to >100 observations over timescales from ∼1 day to ∼8 years. Selection was based on a training sample of 13,221 spectroscopically confirmed type-1 quasars, largely from the SDSS. Using variability alone, colors alone, and combining variability and colors we achieve 91%, 93%, and 97% quasar completeness and 98%, 98%, and 97% efficiency, respectively, with particular improvement in the selection of quasars at 2.7
ISSN:0004-637X
1538-4357