Quantifying Quasar Variability As Part of a General Approach To
  Classifying Continuously Varying Sources
  Robust fast methods to classify variable light curves in large sky surveys
are becoming increasingly important. While it is relatively straightforward to
identify common periodic stars and particular transient events (supernovae,
novae, microlensing), there is no equivalent for non-periodic continuously
varying sources (quasars, aperiodic stellar variability). In this paper we
present a fast method for modeling and classifying such sources. We demonstrate
the method using ~ 86,000 variable sources from the OGLE-II survey of the LMC
and ~ 2,700 mid-IR selected quasar candidates from the OGLE-III survey of the
LMC and SMC. We discuss the location of common variability classes in the
parameter space of the model. In particular we show that quasars occupy a
distinct region of variability space, providing a simple quantitative approach
to the variability selection of quasars.
