Multiphysics Simulations of Collisionless Plasmas

Lautenbach, S.; Grauer, Rainer

doi:10.3389/fphy.2018.00113

Cited by 14 publications

(11 citation statements)

References 38 publications

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“…Multifluid-Maxwell models have been rapidly gaining interest recently in laboratory, space, and astrophysical plasma phyiscs modeling [6,28,17,29,16,30,31,32,33,34,35,36,37]. In this paper, we have developed a locally implicit schemes to integrate the source terms for such systems.…”

Section: Discussionmentioning

confidence: 99%

Exact and Locally Implicit Source Term Solvers for Multifluid-Maxwell Systems

Wang,

Hakim,

et al. 2019

Preprint

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Recently, a family of models that couple multifluid systems to the full Maxwell equations have been used in laboratory, space, and astrophysical plasma modeling. These models are more complete descriptions of the plasma than reduced models like magnetohydrodynamic (MHD) since they are derived more closely from the full kinetic Vlasov-Maxwell system, without assumptions like quasi-neutrality, negligible electron mass, etc. Thus these models naturally retain non-ideal MHD effects like electron inertia, Hall term, pressure anisotropy/nongyrotropy, displacement current, among others. One obstacle to broader application of these model is that an explicit treatment of their source terms leads to the need to resolve rapid processes like plasma oscillation and electron cyclotron motion, even when these are not important. In this paper, we suggest two ways to address this issue. First, we derive the analytic solutions to the source update equations, which can be implemented as a practical, but less generic solver. We then develop a time-centered, locally implicit algorithm to update the source terms, allowing stepping over the fast kinetic time-scales. For a plasma with S species, the locally implicit algorithm involves inverting a local (3S + 3) × (3S + 3) matrix only, thus is very efficient. The performance can be further increased by using the direct update formulas to skip null calculations. We present benchmarks illustrating the exact energy-conservation of the locally implicit solver, as well as its efficiency and robustness for both small-scale, idealized problems and largescale, complex systems. The locally implicit algorithm can be also easily extended to include other local sources, like collisions and ionization, which are difficult to solve analytically.

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Section: Discussionmentioning

confidence: 99%

Exact and Locally Implicit Source Term Solvers for Multifluid-Maxwell Systems

Wang,

Hakim,

et al. 2019

Preprint

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“…Collisionless plasmas, mostly present in astrophysical and space environments, often require a kinetic treatment as given by the Vlasov equation. Unfortunately, the six-dimensional Vlasov equation can only be solved on very small parts of the considered spatial domain (Lautenbach and Grauer 2018). However, in some cases, e.g.…”

Section: Short Comparison Between Microscopic and Macroscopic Processes In Plasmamentioning

confidence: 99%

PIC methods in astrophysics: simulations of relativistic jets and kinetic physics in astrophysical systems

Nishikawa¹,

Duţan

Köhn

et al. 2021

Living Rev Comput Astrophys

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The Particle-In-Cell (PIC) method has been developed by Oscar Buneman, Charles Birdsall, Roger W. Hockney, and John Dawson in the 1950s and, with the advances of computing power, has been further developed for several fields such as astrophysical, magnetospheric as well as solar plasmas and recently also for atmospheric and laser-plasma physics. Currently more than 15 semi-public PIC codes are available which we discuss in this review. Its applications have grown extensively with increasing computing power available on high performance computing facilities around the world. These systems allow the study of various topics of astrophysical plasmas, such as magnetic reconnection, pulsars and black hole magnetosphere, non-relativistic and relativistic shocks, relativistic jets, and laser-plasma physics. We review a plethora of astrophysical phenomena such as relativistic jets, instabilities, magnetic reconnection, pulsars, as well as PIC simulations of laser-plasma physics (until 2021) emphasizing the physics involved in the simulations. Finally, we give an outlook of the future simulations of jets associated to neutron stars, black holes and their merging and discuss the future of PIC simulations in the light of petascale and exascale computing.

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“…Another direction is to apply the kinetic region adaptively. Lautenbach and Grauer [20] adaptively apply the Vlasov, 5-moment or 10-moment models to different regions according to certain criteria. In this paper, we have applied a similar idea and present a new method with an adaptive PIC region embedded into the MHD model for plasma simulations.…”

Section: Introductionmentioning

confidence: 99%

Magnetohydrodynamic with Adaptively Embedded Particle-in-Cell model: MHD-AEPIC

Shou,

Tenishev,

Chen

et al. 2021

Preprint

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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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Multiphysics Simulations of Collisionless Plasmas

Cited by 14 publications

References 38 publications

Exact and Locally Implicit Source Term Solvers for Multifluid-Maxwell Systems

Exact and Locally Implicit Source Term Solvers for Multifluid-Maxwell Systems

PIC methods in astrophysics: simulations of relativistic jets and kinetic physics in astrophysical systems

Magnetohydrodynamic with Adaptively Embedded Particle-in-Cell model: MHD-AEPIC

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