Temperature gradient driven heat flux closure in fluid simulations of collisionless reconnection

The Magnetospheric Multiscale (MMS) mission has given us unprecedented access to high cadence particle and field data of magnetic reconnection at Earth's magnetopause. MMS first passed very near an X‐line on 16 October 2015, the Burch event, and has since observed multiple X‐line crossings. Subsequent 3‐D particle‐in‐cell (PIC) modeling efforts of and comparison with the Burch event have revealed a host of novel physical insights concerning magnetic reconnection, turbulence‐induced particle mixing, and secondary instabilities. In this study, we employ the Gkeyll simulation framework to study the Burch event with different classes of extended, multifluid magnetohydrodynamics (MHD), including models that incorporate important kinetic effects, such as the electron pressure tensor, with physics‐based closure relations designed to capture linear Landau damping. Such fluid modeling approaches are able to capture different levels of kinetic physics in global simulations and are generally less costly than fully kinetic PIC. We focus on the additional physics one can capture with increasing levels of fluid closure refinement via comparison with MMS data and existing PIC simulations. In particular, we find that the ten‐moment model well captures the agyrotropic structure of the pressure tensor in the vicinity of the X‐line and the magnitude of anisotropic electron heating observed in MMS and PIC simulations. However, the ten‐moment model is found to have difficulty resolving the lower hybrid drift instability, which plays a fundamental role in heating and mixing electrons in the current layer.

Section: Discussionmentioning

confidence: 92%

“…A gradient‐based closure to the ten‐moment model has been introduced by Allmann‐Rahn et al. (), where equation is replaced with

\frac{\partial Q_{i j k}}{\partial x_{k}} = - \frac{v_{t}}{false| k_{0} false|} \nabla^{2} false(P_{i j} - p δ_{i j} false),

and k 0 is an adjustable constant. Allmann‐Rahn et al.…”

Section: Discussionmentioning

confidence: 99%

An Extended MHD Study of the 16 October 2015 MMS Diffusion Region Crossing

TenBarge

Juno

et al. 2019

“…In recent years, we have attempted to extend fluid models to incorporate more kinetic effects in magnetospheric systems using higher moment models (Wang et al, ). While these models have been successful in simulating large reconnecting systems (Allmann‐Rahn et al, ; Ng et al, , ; Wang et al, , ), there have not been detailed studies on how well the drift instabilities are represented by the models. Though there is some work on these instabilities in field‐reversed configurations (Hakim & Shumlak, ), existing fluid theory for current sheets (Daughton, ; Pritchett et al, ; Yoon et al, , ) shows some discrepancies with kinetic theory (Daughton, , ; Davidson et al, ) and does not include the pressure tensor which is evolved by the 10‐moment model.…”

Section: Introductionmentioning

confidence: 99%

Drift Instabilities in Thin Current Sheets Using a Two‐Fluid Model With Pressure Tensor Effects

Hakim

Juno

et al. 2019

The integration of kinetic effects in fluid models is important for global simulations of the Earth's magnetosphere. We use a two‐fluid 10‐moment model, which includes the pressure tensor and has been used to study reconnection, to study the drift kink and lower hybrid drift instabilities. Using a nonlocal linear eigenmode analysis, we find that for the kink mode, the 10‐moment model shows good agreement with kinetic calculations with the same closure model used in reconnection simulations, while the electromagnetic and electrostatic lower hybrid instabilities require modeling the effects of the ion resonance using a Landau fluid closure. Comparisons with kinetic simulations and the implications of the results for global magnetospheric simulations are discussed.

“…The 10-moment model is being used in global simulations of magnetospheres (Dong et al, 2019;Wang et al, 2018) and includes the pressure tensor, which is important for balancing the reconnection electric field in collisionless reconnection. The 14-and 21-moment models include the heat flux vector and tensor, respectively, and it has been shown that capturing the heat flux correctly is important for reproducing the reconnection rate observed in kinetic simulations (Allmann-Rahn et al, 2018;Ng et al, 2017). The 35-moment model extends our previous study (Ng et al, 2018) by including the tensor vvvv !…”

Section: Reconstruction Of Distributions In Reconnection Regionsmentioning

confidence: 75%

Reconstruction of Electron and Ion Distribution Functions in a Magnetotail Reconnection Diffusion Region

Chen

Hakim

et al. 2020

In the diffusion region of magnetotail reconnection, particle distributions are highly structured, exhibiting triangular shapes and multiple striations that deviate dramatically from the Maxwellian distribution. Fully kinetic simulations have been demonstrated to be capable of producing the essential structures of the observed distribution functions, yet are computationally not feasible for 3D global simulations. The fluid models used for large‐scale simulations, on the other hand, do not have the kinetic physics necessary for describing reconnection accurately. Our study aims to bridge fully kinetic and fluid simulations by quantifying the information required to capture the non‐Maxwellian features in the distributions underlying the closures used in the fluid code. We compare the results of fully kinetic simulations with observed electron velocity distributions in a magnetotail reconnection diffusion region and use the maximum entropy model to reconstruct electron and ion distributions using various numbers of moments obtained from the simulation. Our results indicate that using only local moments, the maximum entropy model can reproduce many of the features of the distributions: (1) the electron outflow distribution with a tilted triangular structure is reproduced with 21 or more moments in agreement with Ng et al. (2018, https://doi.org/10.1063/1.5041758) and (2) counterstreaming distributions can be captured with the 35‐moment model when the separation in velocity space between the populations is large.