High resolution VLBI polarization imaging of AGN with the maximum entropy method

Abstract

Radio polarisation images of the jets of Active Galactic Nuclei (AGN) can provide a deep insight into the launching and collimation mechanisms of relativistic jets. However, even at VLBI scales, resolution is often a limiting factor in the conclusions that can be drawn from observations. The Maximum Entropy Method (MEM) is a deconvolution algorithm that can outperform the more common CLEAN algorithm in many cases, particularly when investigating structures present on scales comparable to or smaller than the nominal beam size with "super-resolution". A new implementation of the MEM suitable for single-or multiple-wavelength VLBI polarisation observations has been developed and is described here. Monte Carlo simulations comparing the performances of CLEAN and MEM at reconstructing the properties of model images are presented; these demonstrate the enhanced reliability of MEM over CLEAN when images of the fractional polarisation and polarisation angle are constructed using convolving beams that are appreciably smaller than the full CLEAN beam. The results of using this new MEM software to image VLBA observations of the AGN 0716+714 at six different wavelengths are presented, and compared to corresponding maps obtained with CLEAN. MEM and CLEAN maps of Stokes I, the polarised flux, the fractional polarisation and the polarisation angle are compared for convolving beams ranging from the full CLEAN beam down to a beam one-third of this size. MEM's ability to provide more trustworthy polarisation imaging than a standard CLEAN-based deconvolution when convolving beams appreciably smaller than the full CLEAN beam are used is discussed.

Superresolution Full-polarimetric Imaging for Radio Interferometry with Sparse Modeling

“…Image reconstruction with MEM has been practically extended to polarimetry (Holdaway & Wardle 1990;Sault et al 1999;andsee Chael et al 2016 andCoughlan &Gabuzda 2016 for a review of polarimetric MEM techniques).…”

“…In interferometric imaging, another class of widelyused imaging techniques is the Maximum Entropy Methods (MEM), utilizing different functions (named as "entropy terms") to regularize images (see Narayan & Nityananda 1986, for a review). Image reconstruction with MEM has been practically extended to polarimetry (Holdaway & Wardle 1990;Sault et al 1999;andsee Chael et al 2016 andCoughlan &Gabuzda 2016 for a review of polarimetric MEM techniques).…”

Sparse interferometric Stokes imaging under the polarization constraint (Polarized SARA)

“…These methods aim to find an image that maximizes the entropy function while being consistent with the acquired data. As an extension to polarimetric MEM, a special entropy function incorporating this polarization constraint is used (Narayan & Nityananda 1986;Holdaway & Wardle 1990;Coughlan & Gabuzda 2016;Chael et al 2016). Note that these works rely on gradient-descent based techniques which are restricted to solve minimization problems with differentiable objective functions.…”

Faraday Tomography with Sparse Modeling

“…Very recent work demonstrates that regularized maximum likelihood methods which directly solve Equation 7 or 8 often provide higher fidelity reconstructions than the traditional CLEAN approaches for polarimetric imaging, which shares almost equivalent mathematical formulation with Faraday tomography, by utilizing sparse regularizations (Akiyama et al 2017a;Birdi et al 2018) or MEM-based functions (e.g. Chael et al 2016;Coughlan & Gabuzda 2016). Since these methods directly solved the observing equations, it can handle multiple types of data (e.g.…”

“…Akiyama et al 2017a,b). These challenges, which would be common for Faraday tomography with the next generation interferometers, provide active developments of many new highfidelity polarimetric imaging techniques (Chael et al 2016;Coughlan & Gabuzda 2016;Akiyama et al 2017a;Birdi et al 2018), consistently outperforming the traditional CLEAN approaches and its variants.…”