Robust sparse image reconstruction of radio interferometric observations with purify

Next-generation radio interferometers, such as the Square Kilometre Array (SKA), will revolutionise our understanding of the universe through their unprecedented sensitivity and resolution. However, to realise these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed inter\-ferometric images that are limited in quality and scalability for big data. In this work we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers (P-ADMM) algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions, while providing a computational saving and an analytic form. Second, we apply PURIFY to real interferometric observations from the Very Large Array (VLA) and the Australia Telescope Compact Array (ATCA) and find images recovered by PURIFY are higher quality than those recovered by CLEAN. Third, we discuss how PURIFY reconstructions exhibit additional advantages over those recovered by CLEAN. The latest version of PURIFY, with developments presented in this work, is made publicly available.Comment: 22 pages, 10 figures, PURIFY code available at http://basp-group.github.io/purif

Advanced Diagnosis Techniques for Radio Telescopes in Astronomical Applications

The performance of radio telescopes in astronomical applications can be affected by structural variations due to: 1. Misalignment of the feeding structure, resulting in a lateral or axial displacement of the receiver; 2. Wind stress; 3. Gravitational distortion as the antenna is tilted; 4. Thermal distortion with ambient temperature or sunlight. Diagnosis methods are necessary to estimate any deviation of the antenna system from its nominal behavior in order to guarantee the maximum performance. Several approaches have been developed during the years, and among them the electromagnetic diagnosis appears today as the most appealing, because it allows a relatively simple measurement setup and a reduced human intervention. Electromagnetic diagnosis is based on the acquisition of the antenna Far Field Pattern (FFP), with the Antenna Under Test (AUT) working in receiving mode. A natural radio star or a satellite beacon provides the signal source. The acquisition of the FFP typically requires a very large number of field samples to get the complete information about the AUT, and the subsequent measurement process may span over several hours. A prolonged acquisition has significant drawbacks related to the continuous tracking of the source and the inconstancy of the environmental conditions. The purpose of the PhD activity has been focused on an optimized formulation of the diagnosis of radio telescopes aimed at reducing the number of field samples to acquire, and so at minimizing the measurement time. A diagnosis approach has been developed, based on the Aperture Field method for the description of the AUT radiation mechanism. A Principal Component Analysis (PCA) has been employed to restore a linear relationship between the unknowns describing the AUT status and the far field data. An optimal far field sampling grid is selected by optimizing the singular values behavior of the relevant linearized operator. During the activity, a computational tool based on Geometrical Optics (GO) has been developed to improve the diagnosis approach. Indeed, once the Aperture Field is recovered from the inversion of the measured FFP, an additional step is required to assess the AUT status from the phase distribution. Obviously, the computation of the phase distribution should be based on efficient algorithms in order to properly manage electrically large reflectors. The developed GO technique relies on the Fast Marching Method (FMM) for the direct solution of the eikonal equation. A GO approach based on the FMM is appealing because it shows a favorable computational trend. Furthermore, the explicit solution of the eikonal equation opens the possibility to set up an inverse ray tracing scheme, which proves particularly convenient compared to direct ray tracing because it allows to easily select the minimum number of rays to be traced. The FMM is also amenable for parallel execution. In particular, in the present work, the Fast Iterative Method has been implemented on Graphics Processing Units (GPUs). Moreover, the FMM has been accelerated by introducing a tree data structure. The tree allows to manage the mutual interactions between multiple scattering surfaces and the parallelization of the ray tracing step. The method has been numerically tested on simple canonical cases to show its performance in terms of accuracy and speed. Then, it has been applied to the evaluation of the Aperture Field phase required by the reflector diagnosis. During the research activity, the problem of validating the diagnosis algorithms has been also faced. Obviously, a numerical analysis can been carried out to test the model employed to describe the system and to evaluate the performance of the algorithm. To this end, a reliable commercial software exploited to simulate reflector antennas has been exploited. However, to complete the analysis, the experimental validation becomes mandatory, and an experimental outdoor far field test range is required. Accordingly, a test range has been set up thanks to the collaboration with Istituto Nazionale di Astrofisica (INAF) of Naples, Italy. Its realization has involved the full development of the software to drive an Alt-Azimuth positioner and to remotely control the instrumentation. In addition, an upgrade of the internal connections of a Vector Network Analyzer has been performed in order to allow the interferometric acquisition

Interferometric Methods

Future radio telescopes promise great advances in resolution and sensitivity. These include the Square Kilometer Array, a two array instrument, in South Africa and Australia. Similarly, the next generation Very Large Array (ngVLA) is being designed for construction in North America. These arrays all promise exceptional advances in sensitivity, angular resolution, and survey speed. The SKA and ngVLA are both specified to have sensitivities at the level of $\mu$Jy's. The SKA-Low instrument will consist of a huge number of dipoles antennas in Australia which is pushing the bounds of current FX correlator technology with $\mathbb{O}(n^2)$ scaling, where $n$ is the number of antennas. The design proposals for these instruments include a dense core of antennas, necessitating advances in imaging methods for these very dense cores versus more traditionally sparse instruments. Another ambitious experiment is the Hydrogen Epoch of Reionisation Array (HERA) in South Africa which hopes to make the first direct detection of the Epoch of Reionisation through the red-shifted H{\sc i} signal which is a factor of $10^{5}$ smaller than the thermal-like noise. In this thesis, these problems are tackled by re-examining the underlying principles of interferometry. The first working example of a direct imaging correlator is presented which allows images to be formed directly from the voltages off each antenna in a dense array, without an expensive cross-correlation operation as is typically required. A detailed discussion is given of how standard steps in interferometric imaging differ in this new scheme, including calibration. Additionally the first wide field direct imaging correlator is presented, which allows the problems of non-coplanarity to be dealt with for both sparse and dense arrays in a very efficient manner on modern GPU compute hardware. These are, to the best of the authors knowledge, the only working implementations of a direct imaging correlator for generic arrays with no restrictions on the geometry of the array or homogeneity of constituent receiver elements. These new approaches have been published in the scientific literature as discussed in the Declaration. Moving on from this, the closure phase bispectrum is presented as a way of uncovering the cosmological Epoch of Reionisation signal from the H{\sc i} line. This is using the HERA telescope, which consists of a dense core of parabolic antennas in a highly redundant layout. A data reduction and processing pipeline for the HERA telescope is constructed and presented, for use with the bispectrum. Initial results towards a cosmologial limit are reported. The HERA telescope relies on redundancy in its antenna elements for its calibration and measurement strategy. The bispectrum with its unique mathematical propeties, in combination with forward modelling, is shown to be a potent tool for probing departures from the assumed reudundancy. It is shown, through this method, that HERA suffers significant direction-dependent non-redundancies in the dataset used for our analysis, which are extremely difficult to calibrate out. Finally, the problem of wide-field imaging in next generation arrays is tackled through the development and implementation of a new scheme of wide field imaging. This uses a new method of parallelising the problem of wide-field imaging, and is intended for use with the very large datasets that will be produced by upcoming instruments. Two schemes are introduced: $w$-towers, and Improved $w$-towers. The latter generalises the former in combination with advances in optimal convolution theory for the radio astronomy ``gridding'' problem. The theory behind this approach is explored, and a high performance implementation is presented for $w$-towers and Improved $w$-stacking within Improved $w$-towers.ARM Ltd iCase Sponsorshi

CosTuuM: polarized thermal dust emission by magnetically oriented spheroidal grains

We present the new open source C++-based Python library CosTuuM that can be used to generate infrared absorption and emission coefficients for arbitrary mixtures of spheroidal dust grains that are (partially) aligned with a magnetic field. We outline the algorithms underlying the software, demonstrate the accuracy of our results using benchmarks from literature, and use our tool to investigate some commonly used approximative recipes. We find that the linear polarization fraction for a partially aligned dust grain mixture can be accurately represented by an appropriate linear combination of perfectly aligned grains and grains that are randomly oriented, but that the commonly used picket fence alignment breaks down for short wavelengths. We also find that for a fixed dust grain size, the absorption coefficients and linear polarization fraction for a realistic mixture of grains with various shapes cannot both be accurately represented by a single representative grain with a fixed shape, but that instead an average over an appropriate shape distribution should be used. Insufficient knowledge of an appropriate shape distribution is the main obstacle in obtaining accurate optical properties. CosTuuM is available as a standalone Python library and can be used to generate optical properties to be used in radiative transfer applications.Comment: 25 pages, 21 figures, accepted for publication in The Astronomical Journal, CosTuuM is available from https://github.com/SKIRT/CosTuu

Radio Astronomy Image Reconstruction in the Big Data Era

Next generation radio interferometric telescopes pave the way for the future of radio astronomy with extremely wide-fields of view and precision polarimetry not possible at other optical wavelengths, with the required cost of image reconstruction. These instruments will be used to map large scale Galactic and extra-galactic structures at higher resolution and fidelity than ever before. However, radio astronomy has entered the era of big data, limiting the expected sensitivity and fidelity of the instruments due to the large amounts of data. New image reconstruction methods are critical to meet the data requirements needed to obtain new scientific discoveries in radio astronomy. To meet this need, this work takes traditional radio astronomical imaging and introduces new of state-of-the-art image reconstruction frameworks of sparse image reconstruction algorithms. The software package PURIFY, developed in this work, uses convex optimization algorithms (i.e. alternating direction method of multipliers) to solve for the reconstructed image. We design, implement, and apply distributed radio interferometric image reconstruction methods for the message passing interface (MPI), showing that PURIFY scales to big data image reconstruction on computing clusters. We design a distributed wide-field imaging algorithm for non-coplanar arrays, while providing new theoretical insights for wide-field imaging. It is shown that PURIFY’s methods provide higher dynamic range than traditional image reconstruction methods, providing a more accurate and detailed sky model for real observations. This sets the stage for state-of-the-art image reconstruction methods to be distributed and applied to next generation interferometric telescopes, where they can be used to meet big data challenges and to make new scientific discoveries in radio astronomy and astrophysics

Error bounds for digital communication over spatially modulated channels.

Also issued as a Ph.D. thesis in the Dept. of Electrical Engineering, 1968.Bibliography: p.91-93