Turbulence, magnetic reconnection, shocks, and instabilities: non-linear processes in space, laboratory, and astrophysical plasmas

This session focuses on the non-linear processes that take place in space, laboratory and astrophysical plasma. These processes are usually not separated from one another and often go “hand in hand”. Just to mention a few examples, magnetic reconnection is an established ingredient of the turbulence cascade and it is also responsible for the production of turbulence in reconnection outflows; shocks may form in collisional and collisionless reconnection processes and can be responsible for turbulence formation, as for instance in the turbulent magnetosheath; magnetic and velocity-shear driven instabilities triggers plasma turbulence in their non-linear phase and can locally develop in turbulent plasmas. All these non-linear processes are responsible for particle acceleration and plasma heating in the environments where they take place. We are now in a fortunate time for the investigation of these processes, where we can use a combined approach based on simulations and observations together. Simulations can deliver output in a temporal and spatial range of scales going from fluid to electron kinetic. On the observation side, high cadence measurements of particles and fields, high resolution 3D measurements of particle distribution functions and multipoint measurements make it easier to reconstruct the 3D space surrounding the spacecrafts. In this context, the Parker Solar Probe and the Solar Orbiter mission are opening new research scenarios in heliophysics, providing a consistent amount of new data to be analysed. This session welcomes simulations, observational, and theoretical works relevant for the study of the above mentioned plasma processes. Particularly welcome this year, will be works focusing on how non-linear processes accelerate particles and produce heating in collisionless plasmas. We also encourage papers proposing new methods in simulation techniques and data analysis, as for example those rooted in Artificial Intelligence and Machine Learning.