Gaussian Process Modeling Fermi-LAT γ-Ray Blazar Variability: A Sample of Blazars with γ-Ray Quasi-periodicities
Shenbang Yang, Dahai Yan, Pengfei Zhang, Benzhong Dai, Li Zhang
Abstract
Abstract Blazar variability may be driven by stochastic processes. On the other hand, quasi-periodic oscillation (QPO) behaviors were recently reported to be detected in the Fermi-LAT data of blazars. However, the significances of these QPO signals given by traditional Fourier-like methods are still questioned. We analyze γ -ray light curves of the QPO blazars with two Gaussian process methods, CARMA and celerite, to examine the appropriateness of Gaussian processes for characterizing γ -ray light curves of blazars and the existence of the reported QPOs. We collect a sample of 27 blazars with possible γ -ray periodicity and generate their ∼11 yr Fermi-LAT light curves. We apply the Gaussian process models to the γ -ray light curves, and build their intrinsic power spectral densities (PSDs). The results show that in general the γ -ray light curves can be characterized by CARMA and celerite models, indicating that γ -ray variabilities of blazars are essentially Gaussian processes. The resulting PSDs are generally the red noise shapes with slopes between −0.6 and −1.7. Possible evidence for the γ -ray QPOs in PKS 0537−441 and PG 1553+113 are found in the Gaussian process modelings.