Bayesian inference of jet bulk-flow speeds in FRII radio sources

TL;DR

This paper employs Bayesian inference with MCMC to constrain bulk-flow speeds in FRII radio sources, revealing slower kiloparsec-scale jets and consistent parsec-scale speeds, challenging models requiring highly relativistic jets for X-ray emission.

Contribution

It introduces a Bayesian MCMC method to constrain jet Lorentz factors at multiple scales, accounting for intrinsic dispersion in jet features, and provides new empirical constraints on jet speeds.

Findings

Parsec-scale Lorentz factors are consistent with VLBI observations (~10-14).

Kiloparsec-scale Lorentz factors are modest (~1.18-1.49).

Results challenge models requiring gamma ~ 10 for X-ray emission.

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 mean gamma ~ 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 gamma ~ 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.