Fermi Gamma-ray Space Telescope

Investigating the Gamma-ray Variability of Blazars

J. L. Ryan
A. Siemiginowska, M. Sobolewska, J. E. Grindlay

Abstract:

We study the gamma-ray variability of 13 bright blazars observed with Fermi LAT over 6.5 years. We use a new continuous-time autoregressive moving average (CARMA) model to fit Fermi light curves using Bayesian methodology. The order of the CARMA model is selected based on the deviance information criterion. The MCMC simulations of the best model light curves provide the probability density distributions for the CARMA parameters, allowing us to constrain the power spectral density (PSD) of each source. We show, via the simulations, that this method is robust and can be applied to unevenly sampled and noisy data. We also investigate the method's performance in estimating the PSD in comparison to the other standard methods, e.g. periodograms. We present the new constraints on the PSD of these blazars and discuss our findings in the context of the variability models.