Citizen science to identify and analyze coronal jets in SDO/AIA data

Abstract:

Coronal jets are collimated ejections of plasma that are found to be ubiquitous in the solar atmosphere, at different scales and in different regions of the Sun. They are interpreted as the result of energy release in the solar atmosphere when magnetic reconnection involves both closed and open magnetic field lines. Jets are therefore suspected to be associated with the escape of energetic particles from the solar atmosphere and possibly with perturbations of the solar wind. The Atmospheric Imaging Assembly (AIA) on board the Solar Dynamic Observatory (SDO) provides high-cadence and high-resolution images of the solar atmosphere in which coronal jets can be identified and studied. However, the detection of such events via automatic algorithms has been limited and is better achieved by human annotation of the data. In order to detect and catalog coronal jets in the AIA data set, we designed a citizen science project on the Zooniverse platform, where participants can report the precise position and timing of solar jets, along with an indication of their extent. The use of citizen science provides the opportunity to perform this kind of analysis on a large amount of data, and to derive the average values of the jet properties reported by multiple volunteers, removing some of the bias inherent in a single expert observer reporting such properties. This catalog of jet events will provide a useful database for future jet studies, including statistical studies, and a training set for a machine learning approach to the problem of the detection of coronal jets in EUV data sets.