Fully kinetic and hybrid PIC modelling of magnetosheath turbulence: closure and dissipation

Understanding the interactions between the solar wind and the magnetosphere requires multi-scale modelling to resolve magnetohydrodynamic, ion and electron kinetic scales, owing to the collisionless character of plasma turbulence. This leads to computational complexity that reduced models aim to address.

In this study, we investigate decaying turbulence in the magnetosheath by performing comparisons between the ECsim (a fully-kinetic Energy Conserving PIC) model and a computationally lighter model Menura (a hybrid PIC). Menura resolves kinetic ion scales but the influence of massless electrons is provided only via the pressure closure in the generalized Ohm’s law. To ensure meaningful comparisons, we have adjusted the initial conditions using parameters consistent with magnetosheath observations.  

We present a detailed analysis of the pressure-strain interaction terms, electromagnetic work and cross-scales fluxes, demonstrating relatively good agreement between the two models and validating certain turbulent characteristics for Menura. Our findings confirm several established results from fully kinetic Vlasov and PIC simulations, such as connections between coherent structures and energy conversion. Furthermore, we are extending these insights to a novel magnetosheath regime for a hybrid PIC model, which has generally received less attention in such studies. However, discrepancies were also identified, such as Zenitani measure (electromagnetic work done by the non-ideal electric field) and absolute values of energy dissipation which are model-dependent.

In the effort to further improve electron pressure closure, we train a neural network surrogate on ECsim generated data (high fidelity model). We present preliminary results showing consistent scaling for predicted pressure-strain at future simulation time steps as a function of traceless stress, vorticity and the mean square total current density in a lack of data regime.