Authors: Mariana Jeunon (NASA GSFC/CUA), Sophie Musset (APL), Paloma Jol (Leiden Observatory),Ramana Sankar (, University of Minnesota), Lindsay Glesener (University of Minnesota), Lucy Fortson(University of Minnesota), Gregory Fleishman (New Jersey Institute of Technology), Navdeep Panesar (Lockeed Martin Solar and Astrophysics Laboratory), Y. Zhang (University of Minnesota), Georgia de Nolfo (NASA GSFC), Eric Christian (NASA GSFC)

The Sun is the source of energetic particles that fill the heliosphere, interact with the planet’s atmospheres, and impact human activities. The origins of those energetic particles are still under investigation, as well as the mechanisms responsible for their escape from the solar atmosphere where they are energized. Solar jets, collimated ejections of solar plasma along magnetic field lines extending to the interplanetary medium, offer a possible route for particle escape. Coronal solar jets are commonly observed in soft X-rays and extreme ultraviolet (EUV) and are ubiquitous in the solar atmosphere, assuming various shapes, sizes and velocities. To date, autonomous algorithms are not detecting solar jets reliably, and they are usually reported manually by human observers, resulting in an incomplete and inhomogeneous database of jets. In order to produce a reliable, extensive, and consistent database of jets, that will be used to statistically study the jet phenomenon and its relationship to solar energetic particles, we initiated a citizen science project on the Zooniverse platform called “Solar Jet Hunter” whose goal is to explore the huge amount of EUV observations of the Sun in order to identify and characterize solar jets in the dataset. We report on the setup and early results from the Solar Jet Hunter, which was launched in December 2021, with a particular focus on the challenges and benefits of the use of citizen science for our science goals. We discuss how the database of solar jets thus created will then be used to train algorithms to identify solar jets in EUV data.