Minimum energy property of a bounded one- dimensional plasma.
Dynamics, stability and approach to equilibrium of bounded one dimensional collisionless plasma representing minimum energy states with nonlinear Vlasov equation solutions
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Dynamics, stability and approach to equilibrium of bounded one dimensional collisionless plasma representing minimum energy states with nonlinear Vlasov equation solutions
Plasma data from the University of California, San Diego, Auroral Particles experiments on Applied Technology satellites 5 and 6 are used to investigate the dynamics of natural charging events. Both eclipse and daylight charging events are considered, and typical responses are illustrated by data from specific events. Two different physical processes are found to be involved in the charging process. One of these is straightforward: the spacecraft structure potential responds rapidly to changes in the environment, typically changing by hundreds of volts in a few seconds. The other process is more subtle: differential charging and potential barrier formation precede structural charging and determine the time scale; typically, tens of minutes are required for the potential to change by several hundreds of volts. The latter process is found to be predominately responsible for daylight charging on both spacecraft.
The plasma wave instrument on the Dynamics Explorer 1 spacecraft provided measurements of the electric and magnetic components of plasma waves in the Earth's magnetosphere. Four receiver systems processed signals from five antennas. Sixty-seven theses, scientific papers and reports were prepared from the data generated. Data processing activities and techniques used to analyze the data are described and highlights of discoveries made and research undertaken are tabulated.
Thin film and semiconductor microelectronics, radar scattering, radome thermal stress, boundary layer phenomena, guided missile parts, turbulent mixing, antenna systems, and plasma dynamics
A conceptual model of the formation of the plasma sheet and of its dynamical behavior in association with magnetospheric substorms is proposed. The two essential assumptions of the model are that (1) the plasma mantle is the primary source of plasma-sheet particles and (2) the momentum tends to inhibit the rate of magnetic field annihilation (merging) in the tail current sheet. It is found that there exists no steady state configuration for the plasma sheet, which must instead shrink continuously in thickness until the near-earth portion of the current sheet is disrupted by the formation of a magnetic neutral line. The thinning of the plasma sheet and the resulting current-sheet disruption are proposed to be the direct causes of the growth phase and expansion phase, respectively, of substorms.
Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present transformer-based, autoregressive surrogates for efficient prediction of 2D, time-dependent plasma edge state fields. Trained on SOLPS-ITER spatiotemporal data for the KSTAR tokamak, the surrogates forecast electron temperature, electron density, and radiated power over extended horizons. We evaluate model variants trained with increasing autoregressive horizons (1–100 steps) on short- and long-horizon prediction tasks. Longer-horizon training systematically improves rollout stability and mitigates error accumulation, enabling stable predictions over hundreds to thousands of steps and reproducing key dynamical features such as the motion of high-radiation regions. Measured end-to-end wall-clock times show the surrogate is orders of magnitude faster than SOLPS-ITER, enabling rapid parameter exploration. Prediction accuracy degrades when the surrogate enters physical regimes not represented in the training dataset, motivating future work on data enrichment and physics-informed constraints. Overall, this approach provides a fast, accurate surrogate for computationally intensive plasma edge simulations, supporting rapid scenario exploration, control-oriented studies, and progress toward real-time applications in fusion devices.
Theories which describe currents collected by conducting and non-conducting bodies immersed in plasmas have many of their concepts based upon the fundamentals of sheath-potential distributions and charged-particle behavior in superimposed electric and magnetic fields. Those current-collecting bodies (or electrodes) may be Langmuir probes, electric field detectors, aperture plates on ion mass spectrometers and retarding potential analyzers, or spacecraft and their rigid and tethered appendages. Often the models are incomplete in representing the conditions under which the current-voltage characteristics of the electrode and its system are to be measured. In such cases, the experimenter must carefully take into account magnetic field effects and particle anisotropies, perturbations caused by the current collection process itself and contamination on electrode surfaces, the complexities of non-Maxwellian plasma distributions, and the temporal variability of the local plasma density, temperature, composition and fields. This set of variables is by no means all-inclusive, but it represents a collection of circumstances guaranteed to accompany experiments involving energetic particle beams, plasma discharges, chemical releases, wave injection and various events of controlled and uncontrolled spacecraft charging. Here, an attempt is made to synopsize these diagnostic challenges and frame them within a perspective that focuses on the physics under investigation and the requirements on the parameters to be measured. Examples include laboratory and spaceborne applications, with specific interest in dynamic and unstable plasma environments.
The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.
Two phases of substorm-associated magnetospheric dynamics are discussed in terms of particles and fields at synchronous orbit. The first phase corresponds to the 'decreases' of energetic particle flux. The second phase is the conventional expansion phase that begins with the 'onset', characterized in the study by (1) a sudden decrease in the tail current and a return of the inflated magnetosphere to a dipolelike configuration, (2) a sudden shift of trapped high-energy particles toward the tail again following contours of constant B, and at the same time (3) a surge of tail plasma toward the earth as the induced electric field now increases the total convection field.
The objectives of this experiment are to use the Space Technology Experiments Platform (STEP) system to demonstrate the viability of concentrator photovoltaic arrays by: (1) configuring a deployable mast on the STEP pallet with concentrator mass models and some active photovoltaic modules; (2) measuring the array pointing dynamics under normal rotation as well as disturbance conditions; (3) performing an array plasma interaction experiment to determine the steady-state plasma losses under various voltage conditions; and (4) providing active distributed control of the support truss to determine the improvement in dynamic response. Experiment approach and test control and instrumentation are described.
The inverse plasma switch INPIStron was employed for 10kJ/40kV capacitor bank discharge system to produce focused dense plasmas in hypocycloidal-pinch (HCP) devices. A single unit and an array of multiple HCP's were coupled as the load of the pulsed power circuit. The geometry and switching plasma dynamics were found advantageous and convenient for commutating the large current pulse from the low impedance transmission line to the low impedance plasma load. The pulse power system with a single unit HCP, the system A, was used for production of high temperature plasma focus and its diagnostics. The radially running down plasma dynamics, revealed in image converter photographs, could be simulated by a simple snow-plow model with a correction for plasma resistivity. The system B with an array of 8-HCP units which forms a long coaxial discharge chamber was used for pumping a Ti-sapphire laser. The intense UV emission from the plasma was frequency shifted with dye-solution jacket to match the absorption band of the Ti crystal laser near 500 nm. An untuned laser pulse energy of 0.6 J/pulse was obtained for 6.4 kJ/40 kV discharge, or near 103 times of the explosion limit of conventional flash lamps. For both systems the advantages of the INPIStron were well demonstrated: a single unit is sufficient for a large current (greater than 50 kA) without increasing the system impedance, highly reliable and long life operation and implied scalability for the high power ranges above I(sub peak) = 1 MA and V(sub hold) = 100 kV.
Understanding the complex plasma dynamics in ultra-intense relativistic laser–solid interactions is of fundamental importance for applications of laser–plasma-based particle accelerators, the creation of high-energy-density matter, understanding planetary science, and laser-driven fusion energy. However, experimental efforts in this regime have been limited by the lack of accessibility of over-critical densities and the poor spatiotemporal resolution of conventional diagnostics. Over the last decade, the advent of femtosecond brilliant hard X-ray free-electron lasers (XFELs) has opened new horizons to overcome these limitations. Here, for the first time, we present full-scale spatiotemporal measurements of solid-density plasma dynamics, including preplasma generation with tens of nanometer scale length driven by the leading edge of a relativistic laser pulse, ultrafast heating and ionization at the main pulse arrival, the laser-driven blast wave, and transient surface return current-induced compression dynamics up to hundreds of picoseconds after interaction. These observations are enabled by utilizing a novel combination of advanced X-ray diagnostics including small-angle X-ray scattering, resonant X-ray emission spectroscopy, and propagation-based X-ray phase-contrast imaging simultaneously at the European XFEL-HED beamline station.
The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer.
This project evaluated and developed new mathematical and algorithmic techniques capable of handling (in real-time) the growing amounts of data generated by modern fusion research. While existing numerical linear algebra (NLA) methods provide the backbone to classical data analysis and algorithms, these methods fundamentally do not port to distributed architectures nor do they allow low-latency data reduction for control. Motivated by the needs for modern fusion reactors, this project explored and implemented new numerical methods to characterize plasma dynamics, respond in real-time to discharge evolution, and to process massive-scale data accurately and rapidly more fully. This project links expertise in multiple-sensor diagnostics of tokamak plasma dynamics from Columbia University’s Plasma Physics Laboratory with expertise in massive-scale data reduction and extreme data control algorithms at Columbia University’s Data Science Institute. This interdisciplinary project (i) applied machine learning methods, (ii) implemented a properly-trained neural-network for very fast processing of high-speed plasma videography, and (ii) developed the applied mathematical methods, based on randomized-NLA (rNLA) routines, for data analysis, reduction, and real-time control. The Columbia University High Beta Tokamak-Extended Pulse (HBT-EP) facility provided data to test new algorithms and partnership with Columbia University's Data Sciences Institute evaluated the broader use of new algorithms for many challenging control applications.
A new algorithm for molecular dynamics (MD) simulations is developed to optimize plasma particle distributions at given initial temperatures. By combining velocity scaling and reassignment, the method effectively eliminates the initial rise and oscillation in temperatures observed with randomly distributed positions. These rises and oscillations are undesired numerical artifacts observed in conventional plasma MD simulations, arising from unoptimized particle positions. The algorithm demonstrates temperature relaxation without initial rises or oscillations, as well as precise flow velocity relaxation, enabling accurate measurement of relaxation times. The code is accelerated using graphics processing units for parallel processing, enhancing the study of plasma dynamics. The proposed method for distributing physically valid particles in MD simulations enables accurate studies of intrinsic collision processes in plasmas, including the dynamics of strongly coupled plasmas, plasma–wave interactions, and transport phenomena in magnetized plasmas. The paper concludes with a discussion of potential applications and future enhancements to the algorithm.
Abstract Fusion power reactors will generate intense neutron fluxes into plasma-facing and structural materials (SMs). Radiation back-fluxes, generated from neutron–material interactions under these fluxes, can dramatically impact the plasma dynamics, e.g. by seeding runaway electrons during disruptions via Compton scattering of background electrons by wall-emitted gamma radiation. Here, we quantify these back-fluxes, including neutrons, gamma rays, and electrons, using Monte Carlo calculations for a range of SM candidates and first wall (FW) thicknesses. The radiation back-flux magnitudes are remarkably large, with neutron and gamma radiation back-fluxes on the same order of magnitude as the incident fusion neutron flux. Electron back-fluxes are two orders of magnitudes lower, but are emitted at sufficiently high energies to impact the sheath and boundary plasma dynamics. Material configuration plays a key role in determining back-flux magnitudes. The SM chiefly determines the neutron back-flux magnitude, while the FW thickness principally attenuates the gamma ray and electron back-fluxes. In addition to prompt back-fluxes, which are emitted immediately after fusion neutrons impact the surface, significant delayed gamma ray and electron back-fluxes arise from nuclear decay processes in the activated materials. These delayed back-flux magnitudes range from 2% to 7% of the prompt back-fluxes, and remain present during transients when fusion no longer occurs. During disruptions, build-up of delayed gamma radiation back-flux represents potential runaway electron seeding mechanisms, posing additional challenges for disruption mitigation in a power reactor compared with non-nuclear plasma operations. This work highlights the impact of these radiation back-fluxes plasma performance and demonstrates the importance of considering back-flux generation in materials selection for fusion power reactors.
The radial dynamics of the nighttime plasma sheet during substorms is examined. The spatial dependence of plasma sheet variations at different radial distances is studied on the basis of simultaneous recordings from two closely spaced satellites. The simultaneous measurements of the plasma sheet behavior earthward and tailward of r = 15 earth radii confirm substorm models which predict a thinning of the near-earth plasma sheet before the formation of an X-type neutral line, followed by a thickening on the earthward side and a further thinning on the tailward side. Temporal correlations between the plasma sheet variations and substorm development on the ground are studied by obtaining accurate timing of individual substorm expansion onsets. In particular, during multiple onset storms, the near-earth plasma sheet is found to experience a series of multiple expansions and contractions, which usually occur in a one-to-one relationship with ground Pi 2 bursts and are well correlated with auroral zone and low-altitude magnetic disturbances.
We consider a far scrape-off layer (SOL) plasma fluid model of ions that is governed by a Braginskiitype model: a one-dimensional, nonlinear system of advection-diffusion equations coupled with a diffusion equation for neutral particles. Our motivation for studying this system arises from the coupling between the edge plasma and radio-frequency (RF) heating, where solving a far SOL plasma fluid model provides critical insights into edge plasma dynamics. Numerical simulations of plasma fluid models require advanced computational techniques to achieve both efficiency and accuracy, especially when resolving the boundary layer in magnetically confined plasmas. In this work, we propose an implicit-explicit time operator splitting strategy that allows for an efficient solution algorithm, where the diffusive terms are treated semi-implicitly requiring only a linear solve, while the advection part is handled explicitly using a strong-stability-preserving Runge-Kutta (SSP-RK3) scheme. This leads to a fully decoupled system in which the diffusion and advection sub-problems can be solved separately, simplifying the overall solution procedure and allowing for efficient parallelization, which is particularly relevant for exploring the impact of RF heating on the SOL plasma. The main challenge of the discretization is due to the strong coupling between diffusion and advection, particularly through the boundary conditions. This makes implementation of such a scheme in an accurate and stable manner nontrivial. We discuss in detail how to split the equations and manage boundary conditions to maintain stability and well-posedness for each subsystem. We also describe a spatial discretization approach, based on the discontinuous Galerkin finite element method (DG-FEM) and present numerical results for a one-dimensional system.