PKS 2155-304: A Case Study of Blazar Variability Power Spectrum at the Highest Energies and on the Longest Timescales

Abstract

We present the results of our Power Spectral Density (PSD) analysis for the BL Lac object PKS 2155−304, utilizing the nightly-binned long-term light curve from the decade-long monitoring, as well as the minute-binned intra-night light curve from the High Energy Stereoscopic Survey (H.E.S.S.; >200 GeV). The source is unique for exhibiting the shortest flux-doubling timescale at Very High Energy (VHE) among its class and thus provides a rare opportunity to study the particle acceleration on the smallest spatial scales in blazar jets. The light curves are modeled in terms of the Continuous-Time Auto-Regressive Moving Average (CARMA) process. The combined long-term and intra-night PSD extends up to ∼6 decades in the temporal frequency range; unprecedented at the TeV energies for a blazar source. Our systematic approach reveals that PKS 2155−304 shows, on average, a complex shape of variability power spectrum, with more variability power on longer timescales. The long-term variability is best modeled by the CARMA(2,1) process, while the intra-night variability is modeled by a CARMA(1,0) process. We note that the CARMA(1,0) process refers to an Ornstein–Uhlenbeck process where the power-law PSD slope (PSD varies as a function of variability frequency to the power of the negative slope) changes from two to zero, above a certain “characteristic/relaxation” timescale. Even though the derived power spectrum of the intra-night light curve did not reveal a flattening, we speculate such relaxation must occur on timescales longer than a few hours for the source.

Ornstein-Uhlenbeck parameter extraction from light curves of Fermi-LAT observed blazars

“…(7g). Single light curves might very well be modeled by higher order CARMA(p,q) terms, see Goyal (2019) or any amount of OU superpositions, see Takata et al (2018). In this context we aim employing the simplest model to find out whether a large amount of LCs can be adequately described by a simple stochastic process and whether we are able to find a systematic clustering of the OU parameters that we wish to extract from the observed LCs.…”

Detection of periodic signals in AGN red noise light curves: empirical tests on the Auto-Correlation Function and Phase Dispersion Minimization

“…For blazars, broadband PSDs at multiple wavelengths have been measured to roughly follow power-laws (e.g. Goyal et al 2017;Goyal et al 2018;Goyal 2019) or bending power-laws (Chatterjee et al 2018). In this paper, we perform all analyses assuming that the red noise PSD continuum can be modeled as a simple power law or occasionally as a broken power law, as is typical for most AGN data, and/or as is suitable for relatively limited dynamic ranges in temporal frequency.…”

Ornstein-Uhlenbeck parameter extraction from light curves of Fermi-LAT observed blazars

“…(7g). Single light curves might very well be modelled by higher order CARMA(p,q) terms, see Goyal (2019) or any amount of OU superpositions, see Takata et al (2018). In this context we aim employing the simplest model to find out whether a large amount of LCs can be adequately described by a simple stochastic process and whether we are able to find a systematic clustering of the OU parameters that we wish to extract from the observed LCs.…”