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Imaging data from next-generation radio interferometric telescopes with compressive sensing

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If you have a question about this talk, please contact Carola-Bibiane Schoenlieb.

We are about to enter a new era of radio astronomy with new radio interferometric telescopes under design and construction, such as the Square Kilometre Array (SKA), planned for construction in Australia and South Africa. While such telescopes would provide many scientific opportunities, they will also present considerable modelling and data processing challenges. Novel modelling and imaging techniques will be required to overcome these challenges. The theory of compressive sensing is a recent, revolutionary development in the field of information theory, which goes beyond the standard Nyquist-Shannon sampling theorem by exploiting the sparsity of natural images. Compressive sensing suggests a powerful framework for solving linear inverse problems (through sparse regularisation), such as recovering images from the incomplete Fourier measurements taken by radio interferometric telescopes. I will present recent developments in compressive sensing techniques for radio interferometric imaging, which have shown a great deal of promise. Furthermore, by appealing to the theoretical foundations of compressive sensing, I will discuss how telescope configurations can be optimised to further enhance imaging fidelity via the spread spectrum effect that arises in non-coplanar baseline and wide field-of-view settings.

This talk is part of the Applied and Computational Analysis series.

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