Automated Solar Flare Detection and Characterization

Physics

Scientific paper

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Scientific paper

Measurement of the evolution properties of solar flares through their complete cyclic development is crucial in the studies of Solar Physics. From analysis of solar Hα images, we are able to use the Support Vector Machine (SVM) to automatically detect flares, and apply image segmentation techniques to compute the properties of solar flares. We also present our solution for automatically tracking the apparent separation motion of two-ribbon flares and measuring their moving direction and speed in the magnetic fields. From these measurements, with certain assumptions, we can further infer the reconnection electric field as a measure of the rate of magnetic reconnection in the corona. Our automatic procedure is valuable for real-time monitoring of flares evolution.

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