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Register a new userMagnetohydrodynamic with Adaptively Embedded Particle-in-Cell model: MHD-AEPIC
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Space plasma simulations have seen an increase in the use of magnetohydrodynamic (MHD) with embedded Particle-in-Cell (PIC) models. This combined MHD-EPIC algorithm simulates some regions of interest using the kinetic PIC method while employing the MHD description in the rest of the domain. The MHD models are highly efficient and their fluid descriptions are valid for most part of the computational domain, thus making large-scale global simulations feasible. However, in practical applications, the regions where the kinetic effects are critical can be changing, appearing, disappearing and moving in the computational domain. If a static PIC region is used, this requires a much larger PIC domain than actually needed, which can increase the computational cost dramatically. To address the problem, we have developed a new method that is able to dynamically change the region of the computational domain where a PIC model is applied. We have implemented this new MHD with Adaptively Embedded PIC (MHD-AEPIC) algorithm using the BATS-R-US Hall MHD and the Adaptive Mesh Particle Simulator (AMPS) as the semi-implicit PIC models. We describe the algorithm and present a test case of two merging flux ropes to demonstrate its accuracy. The implementation uses dynamic allocation/deallocation of memory and load balancing for efficient parallel execution. We evaluate the performance of MHD-AEPIC compared to MHD-EPIC and the scaling properties of the model to large number of computational cores.
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Energetic particle fluxes in the outer magnetosphere present a significant challenge to modelling efforts as they can vary by orders of magnitude in response to solar wind driving conditions. In this article, we demonstrate the ability to propagate test particles through global MHD simulations to a high level of precision and use this to map the cross-field radial transport associated with relativistic electrons undergoing drift orbit bifurcations (DOBs). The simulations predict DOBs primarily occur within an Earth radius of the magnetopause loss cone and appears significantly different for southward and northward interplanetary magnetic field orientations. The changes to the second invariant are shown to manifest as a dropout in particle fluxes with pitch angles close to 90$^circ$ and indicate DOBs are a cause of butterfly pitch angle distributions within the night-time sector. The convective electric field, not included in previous DOB studies, is found to have a significant effect on the resultant long term transport, and losses to the magnetopause and atmosphere are identified as a potential method for incorporating DOBs within Fokker-Planck transport models.
We find and investigate via numerical simulations self-sustained two-dimensional turbulence in a magnetohydrodynamic flow with a maximally simple configuration: plane, noninflectional (with a constant shear of velocity) and threaded by a parallel uniform background magnetic field. This flow is spectrally stable, so the turbulence is subcritical by nature and hence it can be energetically supported just by transient growth mechanism due to shear flow nonnormality. This mechanism appears to be essentially anisotropic in spectral (wavenumber) plane and operates mainly for spatial Fourier harmonics with streamwise wavenumbers less than a ratio of flow shear to the Alfv{e}n speed, $k_y < S/u_A$ (i.e., the Alfv{e}n frequency is lower than the shear rate). We focused on the analysis of the character of nonlinear processes and underlying self-sustaining scheme of the turbulence, i.e., on the interplay between linear transient growth and nonlinear processes, in spectral plane. Our study, being concerned with a new type of the energy-injecting process for turbulence -- the transient growth, represents an alternative to the main trends of MHD turbulence research. We find similarity of the nonlinear dynamics to the related dynamics in hydrodynamic flows -- to the emph{bypass} concept of subcritical turbulence. The essence of the analyzed nonlinear MHD processes appears to be a transverse redistribution of kinetic and magnetic spectral energies in wavenumber plane [as occurs in the related hydrodynamic flow, see Horton et al., Phys. Rev. E {bf 81}, 066304 (2010)] and differs fundamentally from the existing concepts of (anisotropic direct and inverse) cascade processes in MHD shear flows.
Magnetohydrodynamic turbulence and magnetic reconnection are ubiquitous in astrophysical environments. In most situations, these processes do not occur in isolation, but interact with each other. This renders a comprehensive theory of these processes highly challenging. Here, we propose a theory of magnetohydrodynamic turbulence driven at large scale that self-consistently accounts for the mutual interplay with magnetic reconnection occurring at smaller scales. Magnetic reconnection produces plasmoids that grow from turbulence-generated noise and eventually disrupt the sheet-like structures in which they are born. The disruption of these structures leads to a modification of the turbulent energy cascade, which, in turn, exerts a feedback effect on the plasmoid formation via the turbulence-generated noise. The energy spectrum in this plasmoid-mediated range steepens relative to the standard inertial range and does not follow a simple power law. As a result of the complex interplay between turbulence and reconnection, we also find that the length scale which marks the beginning of the plasmoid-mediated range and the dissipation length scale do not obey true power laws. The transitional magnetic Reynolds number above which the plasmoid formation becomes statistically significant enough to affect the turbulent cascade is fairly modest, implying that plasmoids are expected to modify the turbulent path to dissipation in many astrophysical systems.
A two-dimensional electromagnetic particle-in-cell simulation with the realistic ion-to-electron mass ratio of 1836 is carried out to investigate the electrostatic collisionless shocks in relatively high-speed (~3000 km s^-1) plasma flows and also the influence of both electrostatic and electromagnetic instabilities, which can develop around the shocks, on the shock dynamics. It is shown that the electrostatic ion-ion instability can develop in front of the shocks, where the plasma is under counter-streaming condition, with highly oblique wave vectors as was shown previously. The electrostatic potential generated by the electrostatic ion-ion instability propagating obliquely to the shock surface becomes comparable with the shock potential and finally the shock structure is destroyed. It is also shown that in front of the shock the beam-Weibel instability gradually grows as well, consequently suggesting that the magnetic field generated by the beam-Weibel instability becomes important in long-term evolution of the shock and the Weibel-mediated shock forms long after the electrostatic shock vanished. It is also observed that the secondary electrostatic shock forms in the reflected ions in front of the primary electrostatic shock.
In simulations of partial differential equations using particle-in-cell (PIC) methods, it is often advantageous to resample the particle distribution function to increase simulation accuracy, reduce compute cost, and/or avoid numerical instabilities. We introduce an algorithm for particle resampling called Moment Preserving Contrained Resampling (MPCR). The general algorithm partitions the system space into smaller subsets and is designed to conserve any number of particle and grid quantities with a high degree of accuracy (i.e. machine accuracy). The resampling scheme can be integrated into any PIC code. The advantages of MPCR, including performance, accuracy, and stability, are presented by examining several numerical tests, including a use-case study in gyrokinetic fusion plasma simulations. The tests demonstrate that while the computational cost of MPCR is negligible compared to the nascent particle evolution in PIC methods, periodic particle resampling yields a significant improvement in the accuracy and stability of the results.
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