Bayesian inference of jet bulk-flow speeds in Fanaroff-Riley type II radio sources

Abstract

Radio jet and core data for a complete sample of 98 FRII sources with z < 1 are analysed with a Markov-Chain Monte Carlo (MCMC) model fitting method to obtain constraints on bulk-flow speeds in the beam. The Bayesian parameter-inference method is described and demonstrated to be capable of providing meaningful constraints on the Lorentz factor at both kiloparsec and parsec scales. For both jets and cores we show that models in which some intrinsic dispersion is present in the features' intrinsic prominence, bulk-flow speeds or both provide the best fit to the data. The constraints on the Lorentz factor on parsec scales are found to be consistent with the expected values given VLBI observations and other evidence, with γ ≈ 10-14. On kiloparsec scales, the Lorentz factor is found to be ≈ 1.18 -1.49, in agreement with the results of previous analyses of radio jet data. These values are clearly not consistent with the γ ≈ 10 speeds required by beamed inverse-Compton models of X-ray emission from quasar jets; our results therefore support models that require velocity structure in powerful jets.

X-Ray Emission From Optically Selected Radio-Intermediate and Radio-Loud Quasars

“…The full sample enables accurate parameterization of X-ray luminosity correlations across a wide range of radio properties, notably including the previously sparsely probed but wellpopulated RIQ regime. We are also able to take advantage of recent advances in statistical methods (e.g., Kelly 2007) in our analysis and of newly established constraints on jet properties (e.g., Mullin & Hardcastle 2009) in our modeling. In addition, our use of modern accurate cosmological parameters eliminates a source of systematic error present in some earlier analyses of luminosity correlations.…”

“…A sample of 33 An indication that ∼ 5 • is reasonable is provided by applying the orientation measure from Wills & Brotherton (1995) to the RIQs and RLQs is synthesized with redshift and luminosity distributions drawn from the luminosity function, and with randomly assigned orientations (uniform in sin θ). The intrinsic core prominence (the ratio of core-to-lobe radio flux at low frequencies; i.e., unaffected by beaming) is taken from the Bayesian modeling of FR II sources carried out by Mullin & Hardcastle (2009) and is simulated including intrinsic scatter in core power based on their best-fit model; we also take the typical bulk Lorentz factor γ = 10.5 for core emission from their work. The parameters we adopt are those from Table 5 of Mullin & Hardcastle (2009) for the model excluding low-excitation emission-line objects.…”

“…The intrinsic core prominence (the ratio of core-to-lobe radio flux at low frequencies; i.e., unaffected by beaming) is taken from the Bayesian modeling of FR II sources carried out by Mullin & Hardcastle (2009) and is simulated including intrinsic scatter in core power based on their best-fit model; we also take the typical bulk Lorentz factor γ = 10.5 for core emission from their work. The parameters we adopt are those from Table 5 of Mullin & Hardcastle (2009) for the model excluding low-excitation emission-line objects.…”

Jet and torus orientations in high redshift radio galaxies

“…The most appropriate comparison study in the literature is a Bayesian analysis of the core dominance distribution for a sample of powerful FR II radio sources including both broad and narrow-line objects at z < 1 (Mullin & Hardcastle 2009). This gave Γ = 10 +3 −7 with a dispersion of 0.62 in log R assuming a single value of Γ and a dispersion in intrinsic core dominance.…”

Positive and negative feedback by AGN jets in high‐redshift galaxies

“…This is generally regarded as evidence for highly relativistic speeds of the jet beam with Lorentz factors of ∼ 10. On the kpc scale, if jets do not decollimate and form FR I radio sources (Fanaroff & Riley 1974), they still remain mildly relativistic with typical speeds in the range of 0.5-0.8 c (Mullin & Hardcastle 2009), although X-ray observations may require the presence of a jet spine that is faster than that. While the jet density is not directly measurable from the synchrotron brightness, it can be derived from the kinetic jet powers (cavity powers), speeds and the observable jet radius, finding that it is ≤ 10 −4 m p cm −3 .…”