RHESSI Imaging using Neural Networks
Abstract
Imaging spectroscopy is a powerful diagnostic which allows the physics underlying particle acceleration and transport in solar flares to be explored. Accurate image reconstruction methods are crucial when performing this type of spectroscopy. Fourier imaging instruments such as RHESSI and Solar Orbiter/STIX pose a difficult deconvolution problem due to their sparse sampling of the u-v plane.
Many deconvolution algorithms have been developed to address this problem starting with Högbom's original CLEAN, multi-scale CLEAN, VIS-CLEAN, PIXON and various compressed sensing implementations to name a few. Each of these algorithms have their strengths and weaknesses but no one algorithm has been found to obtain optimal reconstructions under all conditions, specifically altering user defined parameters can yield drastically different results. Additionally many of these algorithms are computationally expensive. Neural networks can model complex systems, it has been shown that sufficiently deep neural networks can represent arbitrarily complex functions. In particular convolutional neural networks (CNNs) have been shown to be particularly powerful in imaging applications. For example CNNs have been trained to perform single image super resolution, velocity field extraction and multi-frame blind deconvolution. Training neural networks is a computationally intensive but once trained evaluating the network for a given input is trivial. A new image deconvolution technique based on CNNs has been developed for use with RHESSI and Solar Obiter/STIX. This method is extremely fast and has only one input, a set of visibilities or equivalently a back-projection. Initial results and comparisons to other imaging algorithms will be presented.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFMSH33E3691M
- Keywords:
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- 7509 Corona;
- SOLAR PHYSICS;
- ASTROPHYSICS;
- AND ASTRONOMYDE: 7519 Flares;
- SOLAR PHYSICS;
- ASTROPHYSICS;
- AND ASTRONOMYDE: 7554 X-rays;
- gamma rays;
- and neutrinos;
- SOLAR PHYSICS;
- ASTROPHYSICS;
- AND ASTRONOMYDE: 7594 Instruments and techniques;
- SOLAR PHYSICS;
- ASTROPHYSICS;
- AND ASTRONOMY