Automated Detection of Oscillatory Behavior in the Corona

Astronomy and Astrophysics – Astronomy

Scientific paper

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Scientific paper

We present an automated analysis package that reads in 3D data cubes and extracts oscillatory behavior metadata. The code extracts specific information through the time dimension of each pixel and outputs just four image files of oscillatory periodicity, duration, start time and peak time that represent the entire data cube.
This metadata shows that there are several factors that are creating these oscillatory behaviors within the corona. Waves, nanoflares and flows are found to be the main contributing factors. Upwardly propagating waves differ significantly within the quiet and active regions of the Sun. Nanoflares are found when small regions of pixels quickly brighten and then dim. Flows are defined as regions of pixels that brighten and this brightening moves over a larger region over time.
This code will be run as part of the SDO Feature Finding Team on selected data from AIA, including pre-flare, post-flare and at times of emerging flux. We will also run this on large quiet Sun data to determine more accurately which factors (waves or nanoflares) are the major contributor to the heating of the corona.

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