Title: Inverse Problems and Machine Learning: the Role of the Mathematics in the Study of Solar Flares

Abstract: Solar flares are intense ex plosive phenomena that occur on the Sun surface and are due to magnetic processes. Although they happen millions of kilometers away from the Earth, the have potentially severe impacts on our planets. Indeed, they can be the trigger of solar storms, which can in turn give rise to electric blackouts and problems in radio and GPS communications. In this talk, I will describe how instruments like the Spectrometer/ Telescope for Imaging X-rays (STIX) measure a limited number of Fourier components of the X-ray radiation emitted during solar flares. Then, I will show how we can reconstruct the image of the flaring X-ray source from STIX data by solving an (ill-posed) inverse problem. Finally, I will provide an overview of the flare forecasting problem and I will describe the machine learning techniques that have been (and are currently) developed for addressing this task.

COHH 3117 or Zoom https://wku.zoom.us/j/95583386311