A Markov Chain Monte Carlo approach for measurement of jet precession in radio-loud active galactic nuclei

Abstract

Jet precession can reveal the presence of binary systems of supermassive black holes. The ability to accurately measure the parameters of jet precession from radio-loud active galactic nuclei is important for constraining the binary supermassive black hole population, which is expected as a result of hierarchical galaxy evolution. The age, morphology, and orientation along the line of sight of a given source often result in uncertainties regarding the jet path. This paper presents a new approach for efficient determination of precession parameters using a two-dimensional Markov chain Monte Carlo curve-fitting algorithm that provides us a full posterior probability distribution on the fitted parameters. Applying the method to Cygnus A, we find evidence for previous suggestions that the source is precessing. Interpreting in the context of binary black holes leads to a constraint of parsec scale and likely sub-parsec orbital separation for the putative supermassive binary.