Compressed sensing and Sequential Monte Carlo for solar hard X-ray imaging
arXiv:1812.08413h-index: 35
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This work provides new inversion techniques for solar X-ray imaging, which could enhance the analysis of solar flare data for astrophysicists.
The authors applied compressed sensing and sequential Monte Carlo methods to reconstruct solar hard X-ray images from visibilities, demonstrating improved reconstruction quality over existing methods on both RHESSI and STIX data.
We describe two inversion methods for the reconstruction of hard X-ray solar images. The methods are tested against experimental visibilities recorded by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and synthetic visibilities based on the design of the Spectrometer/Telescope for Imaging X-rays (STIX).