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Register a new userThe application of compressive sampling to radio astronomy II: Faraday rotation measure synthesis
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Faraday rotation measure (RM) synthesis is an important tool to study and analyze galactic and extra-galactic magnetic fields. Since there is a Fourier relation between the Faraday dispersion function and the polarized radio emission, full reconstruction of the dispersion function requires knowledge of the polarized radio emission at both positive and negative square wavelengths $lambda^2$. However, one can only make observations for $lambda^2 > 0$. Furthermore observations are possible only for a limited range of wavelengths. Thus reconstructing the Faraday dispersion function from these limited measurements is ill-conditioned. In this paper, we propose three new reconstruction algorithms for RM synthesis based upon compressive sensing/sampling (CS). These algorithms are designed to be appropriate for Faraday thin sources only, thick sources only, and mixed sources respectively. Both visual and numerical results show that the new RM synthesis methods provide superior reconstructions of both magnitude and phase information than RM-CLEAN
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Compressive sampling is a new paradigm for sampling, based on sparseness of signals or signal representations. It is much less restrictive than Nyquist-Shannon sampling theory and thus explains and systematises the widespread experience that methods such as the Hogbom CLEAN can violate the Nyquist-Shannon sampling requirements. In this paper, a CS-based deconvolution method for extended sources is introduced. This method can reconstruct both point sources and extended sources (using the isotropic undecimated wavelet transform as a basis function for the reconstruction step). We compare this CS-based deconvolution method with two CLEAN-based deconvolution methods: the Hogbom CLEAN and the multiscale CLEAN. This new method shows the best performance in deconvolving extended sources for both uniform and natural weighting of the sampled visibilities. Both visual and numerical results of the comparison are provided.
Faraday Rotation Measure (RM) Synthesis, as a method for analyzing multi-channel observations of polarized radio emission to investigate galactic magnetic fields structures, requires the definition of complex polarized intensity in the range of the negative lambda square. We introduce a simple method for continuation of the observed complex polarized intensity into this domain using symmetry arguments. The method is suggested in context of magnetic field recognition in galactic disks where the magnetic field is supposed to have a maximum in the equatorial plane. The method is quite simple when applied to a single Faraday-rotating structure on the line of sight. Recognition of several structures on the same line of sight requires a more sophisticated technique. We also introduce a wavelet-based algorithm which allows us to consider a set of isolated structures. The method essentially improves the possibilities for reconstruction of complicated Faraday structures using the capabilities of modern radio telescopes.
We investigate whether the method of wavelet-based Faraday rotation measure (RM) Synthesis can help us to identify structures of regular and turbulent magnetic fields in extended magnetized objects, such as galaxies and galaxy clusters. Wavelets allow us to reformulate the RM synthesis method in a scale-dependent way and to visualize the data as a function of Faraday depth and scale. We present observational tests to recognize magnetic field structures. A region with a regular magnetic field generates a broad disk in Faraday space (Faraday spectrum), with two horns when the distribution of cosmic-ray electrons is broader than that of the thermal electrons. Each magnetic field reversal generates one asymmetric horn on top of the disk. A region with a turbulent field can be recognized as a Faraday forest of many components. These tests are applied to the spectral ranges of various synthesis radio telescopes. We argue that the ratio of maximum to minimum wavelengths determines the range of scales that can be identified in Faraday space. A reliable recognition of magnetic field structures requires the analysis of data cubes in position-position-Faraday depth space (PPF cubes), observed over a wide and continuous wavelength range, allowing the recognition of a wide range of scales as well as high resolution in Faraday space. The planned Square Kilometre Array (SKA) will fulfill this condition and will be close to representing a perfect Faraday telescope. The combination of data from the Low Frequency Array (LOFAR) and the Expanded Very Large Array (EVLA) appears to be a promising approach for the recognition of magnetic structures on all scales. The addition of data at intermediate frequencies from the Westerbork Synthesis Radio Telescope (WSRT) or the Giant Meterwave Radio Telescope (GMRT) would fill the gap between the LOFAR and EVLA frequency ranges.
Rotation measure (RM) synthesis is a widely used polarization processing algorithm for reconstructing polarized structures along the line of sight. Performing RM synthesis on large datasets produced by telescopes like LOFAR can be computationally intensive as the computational cost is proportional to the product of the number of input frequency channels, the number of output Faraday depth values to be evaluated and the number of lines of sight present in the data cube. The required computational cost is likely to get worse due to the planned large area sky surveys with telescopes like the Low Frequency Array (LOFAR), the Murchison Widefield Array (MWA), and eventually the Square Kilometre Array (SKA). The massively parallel General Purpose Graphical Processing Units (GPGPUs) can be used to execute some of the computationally intensive astronomical image processing algorithms including RM synthesis. In this paper, we present a GPU-accelerated code, called cuFFS or CUDA-accelerated Fast Faraday Synthesis, to perform Faraday rotation measure synthesis. Compared to a fast single-threaded and vectorized CPU implementation, depending on the structure and format of the data cubes, our code achieves an increase in speed of up to two orders of magnitude. During testing, we noticed that the disk I/O when using the Flexible Image Transport System (FITS) data format is a major bottleneck and to reduce the time spent on disk I/O, our code supports the faster HDFITS format in addition to the standard FITS format. The code is written in C with GPU-acceleration achieved using Nvidias CUDA parallel computing platform. The code is available at https://github.com/sarrvesh/cuFFS.
RM Synthesis was recently developed as a new tool for the interpretation of polarized emission data in order to separate the contributions of different sources lying on the same line of sight. Until now the method was mainly applied to discrete sources in Faraday space (Faraday screens). Here we consider how to apply RM Synthesis to reconstruct the Faraday dispersion function, aiming at the further extraction of information concerning the magnetic fields of extended sources, e.g. galaxies. The main attention is given to two related novelties in the method, i.e. the symmetry argument in Faraday space and the wavelet technique. We give a relation between our method and the previous applications of RM Synthesis to point-like sources. We demonstrate that the traditional RM Synthesis for a point-like source indirectly implies a symmetry argument and, in this sense, can be considered as a particular case of the method presented here. Investigating the applications of RM Synthesis to polarization details associated with small-scale magnetic fields, we isolate an option which was not covered by the ideas of the Burn theory, i.e. using quantities averaged over small-scale fluctuations of magnetic field and electron density. We describe the contribution of small-scale fields in terms of Faraday dispersion and beam depolarization. We consider the complex polarization for RM Synthesis without any averaging over small-scale fluctuations of magnetic field and electron density and demonstrate that it allows us to isolate the contribution from small-scale field.
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