Multiscale MHD‐Kinetic PIC Study of Energy Fluxes Caused by Reconnection

Abstract

A multi-scale approach provides information about kinetic processes missed by MHD 8 in the description of the energy fluxes from reconnection. 9• Ion bulk energy and enthalpy flows carry the greatest fraction of the energy, a feature common to MHD and kinetic models.• A significant contribution to the energy budget comes from the electron enthalpy flux, an effect missed by MHD models.

Data Mining Reconstruction of Magnetotail Reconnection and Implications for Its First-Principle Modeling

“…It links global reconfigurations of the nightside magnetosphere to kinetic processes on the scales of ion or even electron gyroradii that provide irreversibility for global reconfigurations. As a result, its kinetic particle-in-cell (PIC) simulations describing the full dynamics of electrons and ions (largely protons) and their self-consistent electromagnetic fields [14] are usually limited to the immediate X-line vicinity [15] and the moments after the X-line formation in global magnetohydrodynamic models [16], where the reconnection onset is provided due to numerical or ad hoc plasma resistivity. Moreover, it is very difficult to take into account that the magnetotail itself becomes multiscale prior to the reconnection onset.…”

Energy Flux Densities at Dipolarization Fronts

“…(e.g., Wang et al, 2020;Zhong et al, 2019), that is, ion reflection ahead of the front (e.g., Zhou et al, 2018). This may lead to the expectation that energy transport is dominated by ion physics as well, as indeed suggested by recent numerical simulations which shows that ion kinetic and enthalpy flux carry the greatest energy near the DFs, although electron enthalpy flux contributes to an important portion to the energy budget (Lapenta et al, 2020). However, results from the first in-situ investigation of energy flux densities at the DFs reported in this study contradict such suggestion: in reality, electron enthalpy flux dramatically increases across the DFs and carries the most significant energy.…”

Energy Partition and Balance at Dipolarization Fronts

“…In order to remove effect introduced by data noise or possible random fluctuations, we smooth the data (in a 0.18‐s window for electrons and a 0.6‐s window for ions) and only consider data points with relatively small errors (with ratio of error to quantity difference being smaller than 40%). Local particle heating and acceleration can be directly investigated by examining the following particle energy equations (e.g., Goldman et al., 2016; Lapenta et al., 2020): $$$\frac{\partial {E}_{\mathrm{s}}}{\partial t}=\boldsymbol{E}\cdot {\boldsymbol{J}}_{\mathrm{s}}-\nabla \cdot {\boldsymbol{Q}}_{\mathrm{s}}$$$ $$$\frac{\partial {E}_{\mathrm{b}\mathrm{u}\mathrm{l}\mathrm{k},\mathrm{s}}}{\partial t}=\boldsymbol{E}\cdot {\boldsymbol{J}}_{\mathrm{s}}-\nabla \cdot {\boldsymbol{K}}_{\mathrm{s}}-{\boldsymbol{u}}_{\mathrm{s}}\cdot \nabla \cdot \stackrel{{\leftrightarrow}}{{P}_{\mathrm{s}}}$$$ $$$\frac{\partial {E}_{\mathrm{t}\mathrm{h},\mathrm{s}}}{\partial t}=-\nabla \cdot {\boldsymbol{H}}_{\mathrm{s}}-\nabla \cdot {\boldsymbol{q}}_{\mathrm{s}}+{\boldsymbol{u}}_{\mathrm{s}}\cdot \nabla \cdot \stackrel{{\leftrightarrow}}{{P}_{\mathrm{s}}}$$$ where $${E}_{\mathrm{b}\mathrm{u}\mathrm{l}\mathrm{k},\mathrm{s}}$$, …”