Gaussian Process Modeling $Fermi$-LAT $\gamma$-ray Blazar Variability: A Sample of Blazars with $\gamma$-ray Quasi-periodicities

Abstract

Blazar variability may be driven by stochastic processes. On the other hand, quasi-periodic oscillation (QPO) behaviors are recently reported to be detected in $Fermi$-LAT data of blazars. However, the significances of these QPO signals given by traditional Fourier-like methods are still questioned. We analyze $\gamma$-ray light curves of the QPO blazars with two Gaussian process methods, CARMA and $celerite$, to examine the appropriateness of Gaussian processes for characterizing $\gamma$-ray light curves of blazars and the existence of the reported QPOs. We collect a sample of 27 blazars with possible $\gamma$-ray periodicity and generate their $\sim 11$ years $Fermi$-LAT light curves. We apply the Gaussian process models to the $\gamma$-ray light curves, and build their intrinsic power spectral densities (PSDs). The results show that in general the $\gamma$-ray light curves can be characterized by CARMA and $\text{celerite}$ models, indicating that $\gamma$-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 $\gamma$-ray QPOs in PKS 0537$-$441 and PG 1553$+$113 are found in the Gaussian process modelings.

21 pages, 9 figures, 3 tables. Accepted for publication in ApJ

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