Broadband radio spectro-polarimetric observations of high Faraday rotation measure AGN.

2018
We present broadband polarimetric observations of a sample of high Faraday rotationmeasure (RM) AGN using the VLA telescope from 1 to 2 GHz, and 4 to 12 GHz. The sample (14 sources) consists of compact sources (linear resolution smaller than ~ 5 kpc) that are unpolarized at 1.4 GHz in the NVSS. Total intensity data have been modelled using combination of synchrotron components, revealing complex structure in their radio spectra. Depolarizationmodelling, through the so called qu-fitting, have been performed on the polarized data using an equation that attempts to simplify the process of fitting many different depolarizationmodels that we can divide into two major categories: External Depolarizationand Internal Depolarizationmodels. Understanding which of the two mechanisms are the most representative, would help the qualitative understanding of the AGN jet environment, whether it is embedded in a dense external magnetoionic medium or if it is the jet-wind that causes the high RM and strong depolarization. This could help to probe the jet magnetic field geometry (e.g. helical or otherwise). This new high-sensitivity data, shows a complicated behaviour in the total intensity and polarization radio spectrumof individual sources. We observed the presence of several synchrotron components and Faraday components in their total intensity and polarized spectra. For the majority of our targets, (12 sources) the depolarizationseems to be caused by a turbulent magnetic field. Thus, our main selection criteria (lack of polarization at 1.4 GHz in the NVSS), results in a sample of sources with very large RMs and depolarizationdue to turbulent magnetic fields local to the source. We show how the new qu-fitting technique can be used to probe the magnetised radio source environment and to spectrally resolve the polarized components of unresolved radio sources.
    • Correction
    • Cite
    • Save
    0
    References
    0
    Citations
    NaN
    KQI
    []
    Baidu
    map