Plasma kinetic theory
Plasma kinetic theory is examined. Data cover nonlinear oscillations and plasma turbulence in uniform and nonuniform media.
Kaufman, A. N.↗
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Particle collisionality in scaled kinetic plasma simulations
Kinetic plasma processes, such as magnetic reconnection, collisionless shocks, and turbulence, are fundamental to the dynamics of astrophysical and laboratory plasmas. Simulating these processes often requires particle-in-cell (PIC) methods, but the computational cost of fully kinetic simulations can necessitate the use of artificial parameters, such as a reduced speed of light and ion-to-electron mass ratio, to decrease expense. While these approximations can preserve overall dynamics under specific conditions, they introduce nontrivial impacts on particle collisionality that are not yet well understood. In this work, we develop a method to scale particle collisionality in simulations employing an artificial speed of light and/or an artificial ion-to-electron mass ratio. By introducing species-dependent scaling factors, we independently adjust inter- and intra-species collision rates to better replicate the collisional properties of the physical system. Our approach maintains the fidelity of electron and ion transport properties while preserving critical relaxation rates, such as energy exchange timescales, within the limits of weakly collisional plasma theory. Furthermore, we demonstrate the accuracy of this scaling method through benchmarking tests against theoretical relaxation rates and connecting to fluid theory, highlighting its ability to retain key transport properties. Existing collisional PIC implementations can be easily modified to include this scaling, which will enable deeper insights into the behavior of marginally collisional plasmas across various contexts.
Totorica, S. R. [Princeton Univ., NJ (United State↗
Kinetic Plasma Simulation in the MOOSE Framework: Verification of Electrostatic Particle In Cell Capabilities
In magnetic confinement nuclear fusion reactors, the interaction between the plasma edge and plasma facing components is extremely important. At the plasma edge, a kinetic representation such as particle-in-cell (rather than a fluid representation) is required to accurately capture the plasma behavior. General purpose particle-in-cell plasma simulation capabilities have been developed in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. This new capability is a part of the development of a new MOOSE-based framework for modeling plasma facing components, the Fusion ENergy Integrated multiphys-X (FENIX) framework. In this work, the verification of foundational particle-in-cell capabilities in FENIX is presented. This new plasma simulation capability has three main components: moving particles in discrete steps on the finite element mesh, mapping charge density from the particle's location to the finite element mesh, and solving for the electrostatic potential based on the charge density mapped from particles to the mesh. In this paper, simple verification problems demonstrating each of these new capabilities are presented, and future work includes electromagnetic capabilities and Monte Carlo collisions with neutral gas particles.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Accelerating high-order continuum kinetic plasma simulations using multiple GPUs
Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.
Continuum kinetics↗
Resolution requirements for energy conservation in kinetic plasma simulations
The kinetic codes used to model the coupled dynamics of electromagnetic fields and charged particle transport have requirements for spatial, temporal, and charge resolution. These requirements may vary by the solution technique and scope of the problem. In this report, we investigate the resolution limits in the energy-conserving implicit particle-in-cell code CHICAGO. This report has the narrow aim of determining the maximum acceptable grid spacing for the dense plasmas generated in models of z-pinch target gases and power-flow electrode plasmas. In the 2D sample problem, the plasma drifts without external forces with velocity of 10 cm/µs. Simulations are scaled by plasma density to maintain uniform strides across the plasma and from the plasma to the boundaries. Additionally, the cloud-in-cell technique is used with 400 particles per cell and Δ t = 0.85× the Courant limit. For the linear cloud distribution, the criterion for conserving energy is Δ E/E tot < 0.01 for 50,000 time steps. The grid resolution is determined to crudely be Δx ≲ 3 l s , where l s is the electron collisionless skin depth. For the second-order cloud distribution the criterion is Δ E/E tot < 0.005 yielding Δx ≤ 15 l s . These scalings are functions of the chosen v d , Δ t , particles-per-cell, and number of steps.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Useful operator in plasma kinetic theory.
Operator used in derivation of plasma kinetic equation, expressing integral of pair correlation function for stable and unstable cases via Fourier transform
PLASMA DYNAMICS↗
A new proof of superposition of dressed particles in plasma kinetic theory
Superposition of dressed particles in plasma kinetic theory proved by using generalized stochastic equation for conditional probability density for one particle
Liu, C. H.↗
Accelerating particle-in-cell kinetic plasma simulations via reduced-order modeling of space-charge dynamics using dynamic mode decomposition
We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh. We showcase the efficacy of DMD in modeling the time evolution of current density through a low-dimensional feature space. Not only do such DMD based predictive reduced-order models help accelerate EMPIC simulations, they also have the potential to facilitate investigative analysis and control applications. Here, we demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current density and speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Collision integrals for nonelastic processes in plasma kinetic theory
Collision integrals for nonelastic processes in plasma kinetic theory
Viegas, J. R.↗
High frequency conductivity calculation using the plasma kinetic equation.
Homogeneous, fully ionized plasma HF conductivity computed using kinetic equation, showing application to two-temperature plasma
IONIZED GAS↗
DOE Plasma Science Center - Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems (Final Report DE-SC0001939)
Low temperature plasmas (LTPs) are the plasmas of electron-volt (eV) physics and eV technologies. LTPs have characteristic electron temperatures of a few eV and fractional ionizations that are typically small. Since LTPs have electron temperatures commensurate with the threshold energies of excited states in neutral atoms and molecules, power transfer from electrons to these atoms and molecules efficiently produces activated species (e.g., radicals, excited states, photons). Acceleration of ions in the sheaths of LTPs to energies of tens to hundreds of eV enable activation of surface modifying processes – sputtering, etching, deposition. With such properties, LTPs are often and beneficially used in technological devices, ranging from etching and deposition in microelectronics and solar cell fabrication, to hardening of surgical instruments. LTPs harbor fundamental science issues that are intellectually challenging and rewarding. At the same time, there are enormous societal benefits that are enabled by LTPs. The entire present-day and future information technology infrastructure owes its very existence to LTPs. Renewable energy sources, such as solar cell arrays, could not be economically produced in the absence of deposition and etching by LTPs. In acknowledgment of the importance of LTPs, the DOE Office of Fusion Energy Sciences supported the Plasma Science Center for Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems from August 2009 to July 2021, consisting of an initial 5-year grant, 3 funded extensions and 2 no-cost extensions. This is the final report of the Center in which the productivity of the Center is discussed in terms of publications, impact and personnel. High-lights of the research performed in the Center are provided.
36 MATERIALS SCIENCE↗
Encoding of linear kinetic plasma problems in quantum circuits via data compression
We propose an algorithm for encoding linear kinetic plasma problems in quantum circuits. The focus is on modelling electrostatic linear waves in a one-dimensional Maxwellian electron plasma. The waves are described by the linearized Vlasov–Ampère system with a spatially localized external current that drives plasma oscillations. This system is formulated as a boundary-value problem and cast in the form of a linear vector equation Aψ = b to be solved by using the quantum signal processing algorithm. The latter requires encoding of matrix A in a quantum circuit as a sub-block of a unitary matrix. We propose how to encode A in a circuit in a compressed form and discuss how the resulting circuit scales with the problem size and the desired precision.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Accelerating kinetic plasma simulations with machine-learning-generated initial conditions
Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.
Artificial neural networks↗
Generalized Langmuir Waves in Magnetized Kinetic Plasmas
The properties of unmagnetized Langmuir waves and cold plasma magnetoionic waves (x, o, z and whistler) are well known. However, the connections between these modes in a magnetized kinetic plasma have not been explored in detail. Here, wave properties are investigated by numerically solving the dispersion equation derived from the Vlasov equations both with and without a beam instability present. For omega(sub p)>Omega(sub e), it is shown that the generalized Langmuir mode at oblique propagation angles has magnetic z-mode characteristics at low wave numbers and thermal Langmuir mode characteristics at high wave numbers. For omega(sub p)<Omega(sub e), it is shown that the (oblique) Langmuir mode instead connects to the whistler mode at low wave numbers. The transition from the Langmuir/z mode to the Langmuir/whistler mode near omega(sub p) = Omega(sub e) is rapid. In addition, the effects on wave dispersion and polarization after adding a beam are investigated. Applications of this theory to magnetized Langmuir waves in Earth's foreshock and the solar wind, to waves observed near the plasma frequency in the auroral regions, and to solar type III bursts are discussed.
Willes, A. J.↗
Plasma kinetic processes in a strong d.c. magnetic field
Recent results in the kinetic theory of a strongly magnetized plasma are surveyed. Emphasis is on the electrostatic guiding-center plasma in two dimensions, in both the fluid and 'charged rod' descriptions. The basic kinetic description of the plasma is in terms of the statistically-distributed Fourier coefficients associated with the velocity and 'enstrophy' (charge density) fields. It is a universal tendency in such media for enstrophy to flow to shorter wavelengths but for energy to flow to longer wavelengths. A consequence of the energy flow to longer wavelengths is the generation of long-range order in the form of macroscopic vortices. These kinds of structure have been called 'convection cells' and can be extraordinarily efficient in transporting particles transverse to a magnetic field. The tendency to vortex formation can be disrupted by collisions between particles. Modifications of the Fokker-Planck equation for a plasma produced by a strong dc magnetic field are considered in both two and three dimensions.
Montgomery, D.↗
Plasma kinetic processes in a strong d.c. magnetic field
The electrostatic guiding center approximation is used to describe the kinetic processes of a strongly magnetized tenuous plasma in two dimensions, in both the fluid and charged rod descriptions. The basic kinetic description of the plasma is in terms of the statistically-distributed Fourier coefficients associated with the velocity and enstrophy (charge density) fields. It is shown that the system exhibits a tendency to long range order characterized by macroscopic vorticity concentrations comparable in size to that of the system. These types of structure have historically been called convection cells and can be quite efficient at transporting particles transverse to a magnetic field.
Montgomery, D.↗
Ion and Electron Acceleration in Fully Kinetic Plasma Turbulence
Turbulence is often invoked to explain the origin of nonthermal particles in space and astrophysical plasmas. By means of 3D fully kinetic particle-in-cell simulations, we demonstrate that turbulence in low-β plasmas (β is the ratio of plasma pressure to magnetic pressure) accelerates ions and electrons into a nonthermal energy distribution with a power-law energy range. The ion spectrum is harder than the electron one, and both distributions get steeper for higher β. We show that the energization of electrons is accompanied by a significant energy-dependent pitch-angle anisotropy, with most electrons moving parallel to the local magnetic field, while ions stay roughly isotropic. We demonstrate that particle injection from the thermal pool occurs in regions of high current density. Parallel electric fields associated with magnetic reconnection are responsible for the initial energy gain of electrons, whereas perpendicular electric fields control the overall energization of ions. Our findings have important implications for the origin of nonthermal particles in space and astrophysical plasmas.
79 ASTRONOMY AND ASTROPHYSICS↗
Beyond radiation-hydrodynamics Coupling kinetic plasma and radiation transport
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HOLO, Kinetic plasma↗