Characterizing the Optical Variability of Bright Blazars: Variability-Based Selection of Fermi AGN
John J. Ruan, Scott F. Anderson, Chelsea L. MacLeod, Andrew C. Becker,, T. H. Burnett, James R. A. Davenport, Zeljko Ivezic, Christopher S. Kochanek,, Richard M. Plotkin, Branimir Sesar, J. Scott Stuart

TL;DR
This study demonstrates that optical variability analysis using a damped random walk model effectively identifies blazars and associates them with gamma-ray sources, providing insights into jet physics and improving source classification in large surveys.
Contribution
The paper introduces a variability-based method for selecting blazars using optical light curves, achieving high efficiency and completeness even with shallow survey data.
Findings
High efficiency (>88%) in recovering known Fermi AGN counterparts.
Optical variability timescale in blazars is approximately 3 years in the jet rest frame.
Blazar variability is stochastic and influenced by relativistic beaming.
Abstract
We investigate the use of optical photometric variability to select and identify blazars in large-scale time-domain surveys, in part to aid in the identification of blazar counterparts to the ~30% of gamma-ray sources in the Fermi 2FGL catalog still lacking reliable associations. Using data from the optical LINEAR asteroid survey, we characterize the optical variability of blazars by fitting a damped random walk model to individual light curves with two main model parameters, the characteristic timescales of variability (tau), and driving amplitudes on short timescales (sigma). Imposing cuts on minimum tau and sigma allows for blazar selection with high efficiency E and completeness C. To test the efficacy of this approach, we apply this method to optically variable LINEAR objects that fall within the several-arcminute error ellipses of gamma-ray sources in the Fermi 2FGL catalog.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
