TL;DR
This study analyzes 10-year gamma-ray light curves of selected blazars using multiple spectral methods, revealing characteristic timescales, quasi-periodic oscillations, and differences between blazar subclasses, emphasizing the importance of Monte Carlo simulations for reliable modeling.
Contribution
It provides a comprehensive multi-method spectral analysis of blazar gamma-ray variability, highlighting the limitations of parametric models and identifying characteristic timescales and subclass distinctions.
Findings
Power law indices mostly between 1 and 2.
Detection of a QPO at 3σ significance in PKS 2155-304.
Blazar subclasses separated in the - plane.
Abstract
We present the results of the \textit{Fermi}-LAT 10-years-long light curves (LCs) modeling of selected blazars: six flat spectrum radio quasars (FSRQs) and five BL Lacertae (BL Lacs), examined in 7-, 10-, and 14-day binning. The LCs and power spectral densities (PSDs) were investigated with various methods: Fourier transform, Lomb-Scargle periodogram (LSP), wavelet scalogram, autoregressive moving average (ARMA) process, continuous-time ARMA (CARMA), Hurst exponent (), and the plane. First, with extensive simulations we showed that parametric modeling returns unreliable parameters, with a high dispersion for different realizations of the same stochastic model. Hence any such analysis should be supported with Monte Carlo simulations. For our blazar sample, we find that the power law indices calculated from the Fourier and LSP modeling mostly fall in…
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