# Inferring AGN jet parameters using Bayesian analysis of VLBI data with non-uniform jet model

## TL;DR

This paper introduces a Bayesian method to directly infer physical parameters of AGN jets from VLBI data using an inhomogeneous jet model, avoiding traditional Gaussian template fitting.

## Contribution

It presents a novel Bayesian analysis approach for inhomogeneous jet modeling directly from VLBI data, improving parameter inference accuracy.

## Key findings

- Jet is well described by an inhomogeneous conical model.
- Results favor an electron-positron jet composition.
- Detected counter jet component suggests an external absorber.

## Abstract

Physical parameters of AGN jets observed with Very Long Baseline Interferometry (VLBI) are usually inferred from the core shift measurements or flux and size measured at a peak frequency of the synchrotron spectrum. Both are preceded by modelling of the observed VLBI jet structure with a simple Gaussian templates. We propose to infer the jets parameters using the inhomogeneous jet model directly - bypassing the modelling of the source structure with a Gaussian templates or image deconvolution. We applied Bayesian analysis to multi-frequency VLBA observations of radio galaxy NGC 315 and found that its parsec-scale jet is well described by the inhomogeneous conical model. Our results favour electron-positron jet. We also detected a component in a counter jet. Its position implies the presence of an external absorber with a steep density gradient at close ($r=0.1$ pc) distance from the central engine.