Kinematics of and Emission From Helically Orbiting Blobs in a Relativistic Magnetized Jet

Abstract

We present a general relativistic (GR) model of jet variability in active galactic nuclei due to orbiting blobs in helical motion along a funnel or cone shaped magnetic surface anchored to the accretion disk near the black hole. Considering a radiation pressure driven flow in the inner region, we find that it stabilizes the flow, yielding Lorentz factors ranging between 1.1 and 7 at small radii for reasonable initial conditions. Assuming these as inputs, simulated light curves (LCs) for the funnel model include Doppler and gravitational shifts, aberration, light bending, and time delay. These LCs are studied for quasi-periodic oscillations (QPOs) and the power spectral density (PSD) shape and yield an increased amplitude (∼ 12 %); a beamed portion and a systematic phase shift with respect to that from a previous special relativistic model. The results strongly justify implementing a realistic magnetic surface geometry in Schwarzschild geometry to describe effects on emission from orbital features in the jet close to the horizon radius. A power law shaped PSD with a typical slope of −2 and QPOs with timescales in the range of (1.37 − 130.7) days consistent with optical variability in Blazars, emerges from the simulations for black hole masses M • = (0.5 − 5) × 10 8 M and initial Lorentz factors γ jet,i = 2 − 10. The models presented here can be applied to explain radio, optical, and X-ray variability from a range of jetted sources including active galactic nuclei, X-ray binaries and neutron stars.

Radio and γ-Ray Variability in the BL Lac PKS 0219−164: Detection of Quasi-periodic Oscillations in the Radio Light Curve

“…The method, like the LSP, also attempts to fit sinusoidal waves to the data; however the waves can be localized in both time and frequency domains to account for the transient nature of QPOs (Bravo et al 2014;Torrence & Compo 1998). The method has been widely used in the time series analysis of blazar light curves(e.g., Bhatta et al 2016c;Mohan & Mangalam 2015;Bhatta et al 2013;Hovatta et al 2008). To look for the possible QPOs in the radio light curve of the blazar PKS 0219-164, we employed weighted wavelet z-transform (WWZ), a method described in Foster (1996).…”

“…In such case, relativistic motion of the emission regions along the helical path of the magnetized jets could make a more plausible explanation (e.g., Camenzind & Krockenberger 1992;Mohan & Mangalam 2015). Similarly, in the magnetic flux paradigm for the jet launching in AGNs (see Sikora & Begelman 2013), the magnetic flux accumulation can lead to the formation of so-called magnetically choked accretion flow (MCAF).…”

The Most Compact Bright Radio-loud AGNs. II. VLBA Observations of 10 Sources at 43 and 86 GHz

“…This might result from a projection on the plane of the sky of a helically twisted jet. Helical jets could be triggered by periodic variation in the direction of jet ejection (Linfield 1981;Stirling et al 2003;Zhao et al 2011), Kelvin-Helmboltz instabilities in the jet flow (Hardee 2003;Feng et al 2005;An et al 2010), or the magneto-hydrodynamics of the jet (Camenzind 1986) and can result in quasi-periodic flux density variability (Camenzind & Krockenberger 1992;An et al 2013;Wang et al 2014;Mohan & Mangalam 2015). The 15-GHz VLBA monitoring observation inferred superluminal motions of two jet components from 14-epoch datasets between 1995 and 2010, with a proper motion of 148 ± 15 µas yr −1 (10.1 c) at about 7 mas and 36 ± 13 µas yr −1 (2.47 c) at about 1.5 mas from the core (Lister et al 2013).…”

Signature of inverse Compton emission from blazars

“…The periodogram of each of these simulated light curves is determined using at the same sampling frequencies as that used for the original light curve and at each frequency bin, we construct an empirical distribution function to determine the 3−σ model error at each ordinate. Details of the fitting procedure, model selection using the AIC and the light curve simulations procedure are presented in Mohan et al (2015 and references therein. For a light curve populated by random Gaussian noise, its periodogram ordinates are expected to be χ 2 2 distributed (e.g.…”

“…Finke 2016), and the relative motion between the emitting source and the observer which can introduce systematic variability (e.g. in a helical jet, Mohan & Mangalam 2015;). …”