Experiences with Object Oriented Parallel Plasma PIC Simulations
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One goal of the Numerical Turbulent Transport Project is to model a tokamak (fusion) plasma with 10(sup 8 - 10)(sup 9) particles, to explain anomalous transport of particles and energy.
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Based on the particle-in-cell (PIC) plasma simulation method, the speed-limited PIC (SLPIC) method delivers faster kinetic plasma simulation in cases where the particle distributions evolve slowly compared with the maximum stable PIC timestep. SLPIC thus offers more feasible, fully kinetic simulation in regimes that historically have required fluid approaches, such as magnetohydrodynamic (MHD), two-fluid, or Boltzmann electron treatments. In particular, SLPIC allows an explicit time advance with steps much larger than the inverse plasma frequency, avoiding the instability explicit PIC faces with large timesteps. SLPIC avoids this instability by slowing down fast particles (e.g., electrons) in a way that is rigorously underpinned by an approximate Vlasov equation; unlike MHD, two-fluid, and Boltzmann electron approaches, SLPIC does not fundamentally neglect any first-principles plasma physics, although the choices of the grid cell size, timestep, and number of macroparticles per cell naturally limit the physical phenomena that can be accurately represented. SLPIC can be implemented with minor modifications of a standard PIC code and does not require an implicit time advance. It enables large timesteps in first-principles kinetic plasma simulation of appropriately slow phenomena, and it can handle many of the same complications as PIC, such as boundary conditions and collisions. Finally, in an argon plasma sheath test problem, a SLPIC simulation achieved a speed-up of a factor of 160 over the corresponding PIC simulation, without loss of accuracy.
Space plasmas are usually inhomogeneous and irregular. Particle in cell (PIC) plasma simulations, however, often consider the plasma to be homogeneous and periodic. Here non-periodic PIC simulations with inhomogeneities in the density, temperature and background magnetic field are considered. Boundary conditions and a variable sized grid system are discussed, along with an application to a magnetospheric plasma physics problem in the auroral zone.
Finite-grid (or aliasing) instabilities are pervasive in particle-in-cell (PIC) plasma simulation algorithms, and force the modeler to resolve the smallest (Debye) length scale in the problem regardless of dynamical relevance. These instabilities originate in the aliasing of interpolation errors between mesh quantities and particles (which live in the space–time continuum). Recently, strictly energy-conserving PIC (EC-PIC) algorithms have been developed that promise enhanced robustness against aliasing instabilities. In this study, we confirm by analysis that EC-PIC is stable against aliasing instabilities for stationary plasmas. For drifting plasmas, we demonstrate by analysis and numerical experiments that, while EC-PIC algorithms are not free from these instabilities in principle, they feature a benign stability threshold for finite-temperature plasmas that make them usable in practice for a large class of problems (featuring ambipolarity and realistic ion-electron mass ratios) without the need to consider the size of the Debye length. We also demonstrate that this threshold is absent for the popular momentum-conserving PIC algorithms, which are therefore unstable for both drifting and stationary plasmas beyond a threshold in cell size compared to Debye length. Finite-grid (or aliasing) instabilities are pervasive in particle-in-cell (PIC) plasma simulation algorithms, and force the modeler to resolve the smallest (Debye) length scale in the problem regardless of dynamical relevance. These instabilities originate in the aliasing of interpolation errors between mesh quantities and particles (which live in the space–time continuum). Recently, strictly energy-conserving PIC (EC-PIC) algorithms have been developed that promise enhanced robustness against aliasing instabilities. In this study, we confirm by analysis that EC-PIC is stable against aliasing instabilities for stationary plasmas. For drifting plasmas, we demonstrate by analysis and numerical experiments that, while EC-PIC algorithms are not free from these instabilities in principle, they feature a benign stability threshold for finite-temperature plasmas that make them usable in practice for a large class of problems (featuring ambipolarity and realistic ion-electron mass ratios) without the need to consider the size of the Debye length. Finally, we also demonstrate that this threshold is absent for the popular momentum-conserving PIC algorithms, which are therefore unstable for both drifting and stationary plasmas beyond a threshold in cell size compared to Debye length.
A cylindrical particle-in-cell (PIC) plasma simulation code applicable to plasma densities encountered in low Earth orbit (LEO) is described. The simulated geometries include that of a plain disk and a disk surrounded by a dielectric. Both configurations are mounted upon a ground plate in contact with a plasma environment. Techniques allowing simulation of dielectric charging using PIC time scales are discussed. Current versus voltage characteristic curves are calculated and the results are compared to experimental data.
Particle-in-cell (PIC) algorithms are widely used for the simulation of kinetic plasmas. PIC algorithms account for the interaction between charged particles in a plasma and the electromagnetic field in ambient space, including self-field interactions. The objective of this article is to study the error in charged particle trajectories present in finite-element (FE)-based PIC algorithms on unstructured meshes. We study how the trajectory error behaves according to the FE mesh resolution and the matrix solver employed in the FE algorithm. The study is performed by considering a trajectory established by a parabolic electric potential and an axial magnetic force acting on the charged particle. Under a proper choice combination of electric and magnetic field parameters, the 2-D particle trajectories comprise closed orbits. Numerical errors cause small perturbations on the trajectories, with cumulative effects. As a result, the resulting orbital trajectories exhibit distortions including spurious apsidal precession. These distortions provide a clear imprint of the numerical error. Here, we also study the numerical error in a quantitative fashion by computing the distance norm between the trajectories obtained by the exact fields and numerical fields.
Ion-driven destabilization of a toroidal electron plasma in a small aspect ratio axisymmetric toroidal device is reported for A r + ions of different initial density values using a high fidelity 3D3V PIC solver. Stability of a recently discovered quiescent quasi-steady state (QQS) of a toroidal electron plasma obtained from “seed” solution as a result of entropy extremization at zero inertia is addressed in the presence of a small ion population. An initial value (f0) of the ion fraction (f = n i / n e) and the corresponding secondary electrons are “preloaded” into the system after the electron plasma attains a QQS state. This procedure is regarded as a proxy to the conventional production of ions in the experimental devices via impact ionization. The resulting electron plasma exhibits destabilized “center of charge motion” (m = 1) along with higher order harmonics with dominant power in the second harmonic. Gradual loss of ions (and also electrons) is observed resulting in time varying f values. Beyond a certain value of f0 (≥ 0.005), growth in wall probe current is observed, which saturates at later simulation time due to the loss of particles. In conclusion, trajectories of ion particles indicate ion trapping in the potential well, which is qualitatively similar to the ion resonance instability in pure electron plasmas.
A three-dimensional electrostatic particle-in-cell (PIC) plasma simulation code has been developed on coarse-grain distributed-memory massively parallel computers with message passing communications. Our implementation is the generalization to three-dimensions of the general concurrent particle-in-cell (GCPIC) algorithm. In the GCPIC algorithm, the particle computation is divided among the processors using a domain decomposition of the simulation domain. In a three-dimensional simulation, the domain can be partitioned into one-, two-, or three-dimensional subdomains ("slabs," "rods," or "cubes") and we investigate the efficiency of the parallel implementation of the push for all three choices. The present implementation runs on the Intel Touchstone Delta machine at Caltech; a multiple-instruction-multiple-data (MIMD) parallel computer with 512 nodes. We find that the parallel efficiency of the push is very high, with the ratio of communication to computation time in the range 0.3%-10.0%. The highest efficiency (> 99%) occurs for a large, scaled problem with 64(sup 3) particles per processing node (approximately 134 million particles of 512 nodes) which has a push time of about 250 ns per particle per time step. We have also developed expressions for the timing of the code which are a function of both code parameters (number of grid points, particles, etc.) and machine-dependent parameters (effective FLOP rate, and the effective interprocessor bandwidths for the communication of particles and grid points). These expressions can be used to estimate the performance of scaled problems--including those with inhomogeneous plasmas--to other parallel machines once the machine-dependent parameters are known.
A three-dimensional electrostatic particle-in-cell (PIC) plasma simulation code has been developed.
The basic physics involving the interaction of a high voltage sphere with a LEO-Plasma was investigated via computer experiments. Two approaches were used: the fluid description and the more general particle pushing method. Both techniques displayed qualitatively similar features. Thus, the initial time-dependent response of the plasma predicted by the fluid model, including the initial current surge and sheath formation, the formation of ion and electron density shells about the sphere with a double layer potential structure, and the subsequent propagation of the density shells away from the sphere. The PIC results also displayed an oscillatory character and slightly different time constants for the growth and decay mechanisms involved.
The advent of massively parallel supercomputers, with their distributed-memory technology using many processing units, has favored the development of highly-scalable local low-order solvers at the expense of harder-to-scale global very high-order spectral methods. Indeed, FFT-based methods, which were very popular on shared memory computers, have been largely replaced by finite-difference (FD) methods for the solution of many problems, including plasmas simulations with electromagnetic Particle-In-Cell methods. For some problems, such as the modeling of so-called “plasma mirrors” for the generation of high-energy particles and ultra-short radiations, we have shown that the inaccuracies of standard FD-based PIC methods prevent the modeling on present supercomputers at sufficient accuracy. Here, we demonstrate here that a new method, based on the use of local FFTs, enables ultrahigh-order accuracy with unprecedented scalability, and thus for the first time the accurate modeling of plasma mirrors in 3D.
Two dimensional plasma particle simulations of the evolution of large amplitude circularly polarized Alfven waves propagating parallel to the magnetic field show that the waves decay via both one- and two- dimensional parametric decay instabilities. For parameters studied, one-dimensional processes dominate the simulations, but two-dimensional decay processes, including the recently predicted filamentation instability are also observed. The daughter waves generated by the parametric decay are primarily damped by the ions, leading to ion heating. The parametric decay processes efficiently convert the ordered fluid ion motion in the Alfven wave into ion thermal energy. These processes may be important for the dissipation of Alfven waves in the solar wind, the corona and other space plasma environments. The computations were performed on the Intel Touchstone parallel supercomputer.
We present a concept of a plasma lens in a parametric resonance ionization cooling (PIC) for extra cooling of muon colliders. The PIC concept has been developed to overcome most aberrations. However, parasitic non-linear aberrations which is induced in an ionization cooling material still reduce a dynamic aperture of the PIC. The plasma lens generates an azimuthally symmetric focusing field in gas-filled RF cavities that is several orders of magnitude stronger than the conventional superconducting magnets. It allows for reduction of the beam size at the beam expansion points. This reduces the size of the aberrations and therefore greatly simplifies their compensation.
Abstract The lack of understanding of the azimuthal instability and the resulting electron anomalous transport limits further improvement of Hall thrusters. Compared to theoretical and experimental approaches, the numerical particle-in-cell (PIC) simulation is a suitable and powerful tool, which has been widely applied to investigate the azimuthal instability, and great progress has been made in the past decades. However, PIC simulations are intrinsically computationally expensive, and it is realized that the Hall thruster azimuthal instability has a three dimensional nature. Therefore, massive 3D PIC simulation must be carried out to completely reveal the mechanism of the instability. In this paper, the effect of plasma initialization on 3D PIC simulation of Hall thruster azimuthal instability is studied as a starting point. It is found that by initializing with ion density and velocity fitting functions to the steady-state simulation results, a faster convergence can be obtained and the computational time can be reduced by about 1.5 times. Typical fitting functions of ion density, drifting velocity, and temperature are given, and the influence of different initialization profiles is presented.
A new method based on a re-splitting δ f technique is proposed to mitigate the cancellation problem in electro-magnetic gyrokinetic PIC simulation. This new scheme, together with the pull-back mitigation (PBM) scheme (Mishchenko et al., 2014), have recently been implemented in the GEM code (Chen et al., 2003). These two algorithms are systematically compared with the original GEM algorithm for the simulation of the ion temperature gradient (ITG) mode, the kinetic ballooning mode (KBM), the toroidal Alfvén eigenmode (TAE) and the energetic particle mode (EPM). The three algorithms agree well for all of these modes. Moreover, both the re-splitting method and PBM can mitigate the cancellation problem and improve the computational efficiency.