We expand on the dispersion analysis of polarimetry maps toward applications to interferometry data. We show how the filtering of low spatial frequencies can be accounted for within the idealized Gaussian turbulence model, initially introduced for single-dish data analysis, to recover reliable estimates for correlation lengths of magnetized turbulence, as well as magnetic field strengths (plane-of-the-sky component) using the Davis–Chandrasekhar–Fermi method. We apply our updated technique to TADPOL/CARMA data obtained on W3(OH), W3 Main, and DR21(OH). For W3(OH), our analysis yields a turbulence correlation length δ ≃ 19 mpc, a ratio of turbulent-to-total magnetic energy 〈B〉_^2_t/〈B^2〉 ≃ 0.58, and a magnetic field strength B_0 ~ 1.1 mG for...
We present a novel statistical analysis aimed at deriving the intrinsic shapes and magnetic field o...
Context. Observations of Zeeman split spectral lines represent an important approach to derive the s...
We adopt the deep learning method casi-3d (convolutional approach to structure identification-3D) to...
We expand on the dispersion analysis of polarimetry maps toward applications to interferometry data....
We apply our technique on the dispersion of magnetic fields in molecular clouds to high spatial reso...
We expand our study on the dispersion of polarization angles in molecular clouds. We show how the ef...
We describe a method for determining the dispersion of magnetic field vectors about large-scale fiel...
In this paper, we use our recent technique for estimating the turbulent component of the magnetic fi...
Polarimetric maps have been used for the characterization of the magnetic field in molecular clouds....
The dynamical state of star-forming molecular clouds cannot be understood without determining the st...
The mean plane-of-sky magnetic field strength is traditionally obtained from the combination of pola...
D.F.G. thanks the European Research Council (ADG-2011 ECOGAL), and brazilian agencies CNPq (No. 3003...
We studied Faraday rotation measure (RM) in turbulent media with the rms Mach number of unity, using...
New visible polarization data combined with existing IR and FIR polarization data are used to study ...
Magnetic fields in the turbulent interstellar medium (ISM) are a key element in understanding Galact...
We present a novel statistical analysis aimed at deriving the intrinsic shapes and magnetic field o...
Context. Observations of Zeeman split spectral lines represent an important approach to derive the s...
We adopt the deep learning method casi-3d (convolutional approach to structure identification-3D) to...
We expand on the dispersion analysis of polarimetry maps toward applications to interferometry data....
We apply our technique on the dispersion of magnetic fields in molecular clouds to high spatial reso...
We expand our study on the dispersion of polarization angles in molecular clouds. We show how the ef...
We describe a method for determining the dispersion of magnetic field vectors about large-scale fiel...
In this paper, we use our recent technique for estimating the turbulent component of the magnetic fi...
Polarimetric maps have been used for the characterization of the magnetic field in molecular clouds....
The dynamical state of star-forming molecular clouds cannot be understood without determining the st...
The mean plane-of-sky magnetic field strength is traditionally obtained from the combination of pola...
D.F.G. thanks the European Research Council (ADG-2011 ECOGAL), and brazilian agencies CNPq (No. 3003...
We studied Faraday rotation measure (RM) in turbulent media with the rms Mach number of unity, using...
New visible polarization data combined with existing IR and FIR polarization data are used to study ...
Magnetic fields in the turbulent interstellar medium (ISM) are a key element in understanding Galact...
We present a novel statistical analysis aimed at deriving the intrinsic shapes and magnetic field o...
Context. Observations of Zeeman split spectral lines represent an important approach to derive the s...
We adopt the deep learning method casi-3d (convolutional approach to structure identification-3D) to...