Abstracts

Siddharth Bachoti, Auburn University

Title: Interplay of dust ordering and potential structures in magnetized low temperature plasmas

Abstract: Imposed ordering (first observed in the Magnetized Dusty Plasma eXperiment (MDPX) [1]) occurs when micron-sized dust particles form 4-fold symmetric structures, aligned with the square gridded conducting mesh. Dust particles move along elongated electric potential structures from the mesh in a magnetic field, revealing plasma potential structures. The strength and morphology of these structures vary with magnetic field, neutral pressure, and mesh geometry. We aim to quantify dust phases from 6-fold self-ordering to 4-fold imposed-ordering as magnetization increases using different mesh geometries, characterizing the plasma potential structures. Results from recent experiments in MDPX are presented.

Acknowledgments: This work is supported by the NSF and the US Department of Energy.
References:
[1] E. Thomas, et al., Phys. Plasmas, 22, 030701 (2015)

Trevor Bowen, UC Berkeley

Title: What Heats the Solar Wind? Perspectives and Progress from Parker Solar Probe

Abstract: The processes underlying collisionless heating and dissipation are fundamental problems in plasma and astrophysics research. In situ observations from spacecraft in collisionless plasma environments provide significant constraints on how these processes operate and their relative efficiency as a means for dissipating turbulent energy. Here we highlight the importance of understanding kinetic phase space signatures as a means to constrain collisionless dissipation mechanisms via approximation by diffusive approximation schemes. We highlight recent progress in understanding signatures of stochastic heating, cyclotron resonance, and Landau damping via observations from the Parker Solar Probe (PSP) mission. Importantly, our observations reveal that a range of heating mechanisms are likely important in explaining observed phase-space plasma signatures.

Seth Dorfman, Space Science Institute

Title: The CHIMERAS Project: Design Framework for the Collisionless HIgh-beta Magnetized Experiment Researching Astrophysical Systems

Abstract: From the near-Earth solar wind to the intracluster medium of galaxy clusters, collisionless, high-beta, magnetized plasmas pervade our universe. Energy and momentum transport from large-scale fields and flows to small scale motions of plasma particles is ubiquitous in these systems, but a full picture of the underlying physical mechanisms remains elusive. The transfer is often mediated by a turbulent cascade of Alfvénic fluctuations as well as a variety of kinetic instabilities; these processes tend to be multi-scale and/or multi-dimensional, which makes them difficult to study using spacecraft missions and numerical simulations alone (Dorfman et al. 2023; Lichko et al. 2020, 2023). Meanwhile, existing laboratory devices struggle to produce the collisionless, high ion beta (βi ≳ 1), magnetized plasmas across the range of scales necessary to address these problems. For example, direct observation of the Alfvén wave parametric instability, an important non-linear process that limits the solar wind parameter space (Bowen, et al, 2018), has not been achieved in the laboratory in part due to Alfvén wave damping (Li, et al, 2024).

As envisioned in recent community planning documents (Carter et al. 2020; Milchberg and Scime 2020; Baalrud et al. 2020; Dorfman et al. 2023; NASEM 2024), it is important to build a next generation laboratory facility to create a βi ≳ 1, collisionless, magnetized plasma in the laboratory for the first time. A Working Group has been formed and is actively defining the necessary technical requirements to move the facility towards a construction-ready state. Recent progress includes development of target parameters and diagnostic requirements as well as identification of a need for source-target device geometry. As the working group is already leading to new synergies across the community, we anticipate a broad community of users funded by a variety of federal agencies (including NASA, DOE, and NSF) to make copious use of the future facility.

References:
Dorfman et al. 2023
Lichko et al. 2020, 2023
Bowen, et al, 2018
Li, et al, 2024
Carter et al. 2020
Milchberg and Scime 2020
Baalrud et al. 2020
NASEM 2024

Alessandro Geraldini, EPFL SPC

Title: Characteristics and constraints of plasma sheaths at shallow magnetic field incidence

Abstract: Just like all laboratory plasmas, the plasma in a fusion device is intertwined with its solid boundaries. Far away from the walls, transport is successfully described and simulated by fluid or kinetic models which average over the quasi-circular Larmor orbits of charged particles, and solve for the electric field via quasineutrality. Turbulence in the edge region has emerged as crucial in determining the overall confinement in the device, and the wall ultimately sets the boundary conditions. Yet, due to the typically grazing incident angle of the magnetic field lines, ion gyro-orbits deform to non-circular in a region near the wall called the magnetic presheath, as the electric field directed towards the target becomes so large and inhomogeneous, at the gyro-radius length scale, that it causes sheared ExB flows tangential to the target of the order of the thermal velocity.

In order to reflect electrons and keep the outflow ambipolar, the electric field even closer to the target, within the actual Debye sheath, becomes inhomogeneous on the scale of the Debye length, thus breaking quasineutrality and possibly also deforming electron gyro-orbits. I will present a theoretical framework and a numerical scheme that allow to iteratively and quickly obtain numerical solutions of the steady state of the magnetised plasma sheath (Debye sheath + magnetic presheath) for shallow magnetic field incidence at the wall, relevant to fusion devices. The code also returns the ion distribution function reaching the target, important for sputtering, and the reflected electron distribution function, which determines the net electron fluxes to the wall. I will also outline the necessary conditions for a monotonic and steady-state sheath solution to exist, and discuss the possible implications of the nontrivial constraints that emerge when gradients tangential to the target affect transport to the wall.

Renaud Gueroult, CNRS

Title: Light drag in plasmas

Abstract: Wave drag phenomena refer to the modifications of wave properties induced by the medium's motion, as first observed by Fizeau for visible light propagating through a water flow. In isotropic dielectrics these phenomena are classically known to scale as the Fresnel drag coefficient (ng-1/n), with ng and n the group and refractive index, respectively. For typical dielectrics this drag coefficient is typically of order 1, and dragging effects are accordingly small and generally negligible.

There are however a number of reasons to believe this may not hold true in plasmas, and thus that wave drag may play a role on wave physics. First, plasmas support waves with low group velocity, leading to large group index and thus to large drag coefficient, similarly to those leveraged to observe these effects with visible light in slow light media [1]. Second, magnetized plasmas are anisotropic media, leading to a richer phenomenology.

In this talk I will discuss what we have learned on wave drag in magnetized plasmas, as well as how these effects may be observed in laboratory experiments and notably LAPD.

References:
[1] Franke-Arnold et al., Rotary Photon Drag Enhanced by a Slow-Light Medium (2011), Science, 333, 65

Yashika Ghai, ORNL

Title: A First-Principles-informed Framework for Runaway Electron–Whistler Interactions in Tokamak

Abstract: Resonant interactions between high-energy runaway electrons (REs) and whistler waves can significantly alter RE dynamics by enhancing pitch-angle scattering and increasing synchrotron radiation losses. Recent DIII-D experiments have demonstrated that externally launched whistler waves can mitigate RE-induced damage to plasma-facing components [1,2]. However, a comprehensive framework for modeling RE transport in the presence of whistler fields remains underdeveloped.

To address this gap, we couple two advanced computational tools: AORSA, which computes whistler eigenmodes for a given plasma equilibrium, and KORC, a kinetic orbit code that tracks full orbit RE trajectories in prescribed wave fields. To the best of our knowledge, this is the first time such simulations have been performed that capture toroidal mode coupling and full-wave structure from AORSA, while using full-orbit dynamics in KORC to resolve pitch-angle scattering in realistic tokamak equilibria.

Results from AORSA+KORC simulations show that the statistical moments—mean, variance, skewness, and kurtosis—of RE pitch-angle and normalized kinetic energy displacements increase rapidly in the presence of whistler fields, indicating REs scattering to large pitch angles due to wave-particle interactions. We observe energy-dependent changes in the ensemble-averaged RE kinetic energy, with the strongest enhancement occurring for initial energies in the 1–5 MeV range, reinforcing the possibility of resonant energy transfer. Our findings also indicate an energy-dependent scaling for RE transport in pitch angle and kinetic energy, that varies between diffusive, sub-diffusive and super-diffusive for different values of the initial runaway electron kinetic energy. Further analysis of RE pitch-angle and energy distributions over time provides deeper insight into the underlying transport mechanisms.

By revealing the non-diffusive character of RE–whistler interactions, this work advances the theoretical understanding of RE transport and lays the foundation for developing targeted mitigation strategies in next-generation tokamak experiments.

References:
[1] D. A. Spong et al., Phys. Rev. Lett., 120, 155002 (2018)
[2] W. W. Heidbrink at al., Plasma Phys. Control. Fusion, 61, 14007 (2019)

Saeid Houshmandyar, University of Texas at Austin

Title: Feasibility study of non-Maxwellian distribution Measurement using an oblique view in ITER electron cyclotron emission diagnostics

Abstract: A longstanding discrepancy between electron temperatures measured by electron cyclotron emission (ECE) diagnostics and Thomson scattering (TS) has been attributed to non-Maxwellian features in the electron momentum distribution. Initially observed in JET and TFTR tokamaks, this discrepancy manifests as higher ECE temperatures (TECE) compared to TS temperatures (TTS) when central electron temperatures exceed 7 keV. However, JET-DT experiments have revealed cases where TECE can either exceed or fall below TTS. These inconsistencies are expected to become more pronounced in ITER, where the temperature is projected to reach ~25 keV.

The performance of the oblique view for the ITER-ECE diagnostics has been reassessed. GENRAY 3D ray-tracing has been utilized to calculate emission, absorption, and radiation transport for both thermal and nonthermal electron velocity distribution functions (EVDF). Non-Maxwellian distributions were generated by distorting EVDF from the Maxwellian distribution in the range of u < 1.5uth.

The simulated ECE spectra across multiple cyclotron frequency harmonics suggest that the O-mode emission at the first harmonic and the X-mode emission at the second harmonic may yield unreliable temperature measurements. However, emissions at higher harmonics can provide accurate temperature information using ECE instruments. Furthermore, the analysis shows that the locations of distortions in the EVDF with respect to EC harmonic resonances have a significant effect on the nature of the non-thermal emissions. Additionally, the simulation suggests that non-thermal emissions may not be detected in the radiation temperature spectra at the oblique angle due to Doppler broadening dominating the relativistic effects on the radiation temperature.

Armand Keyhani, University of Wisconsin-Madison

Title: Anomalous Ion Heating in Ultra-Low Safety-Factor Toroidal Pinch Plasmas

Abstract: Ultra-Low-q (ULq) plasmas are defined as having an edge safety-factor q(a) between 0 and 1. This regime lies between the reversed-field pinch which has q(a)<0 and the tokamak which has q(a)>2. ULq plasmas are poorly understood because tokamaks are increasingly susceptible to external kink instability as q(a) approaches 2. In MST, the thick conducting shell maintains global stability, and recently implemented high-bandwidth programmable power supplies allow for steady ULq operation with plasma current up to 300 kA and toroidal field up to 0.13 T. Magnetic fluctuations, electron density, and impurity ion temperatures (Ti) in ULq plasmas with 0.4
Ti is nearly constant and has a non-linear dependence on q(a). Ti generally increases as q(a) decreases and peaks at q(a)~0.65. Ti also has a strong non-linear dependence on average plasma density where a factor of 4X decrease in density can cause a factor of 10X increase in Ti. As toroidal field and plasma current are increased at constant q(a), Ti increases linearly, global resistance remains nearly constant, and Ohmic input power increases quadratically. Results suggest that the ion heating is associated with broadband magnetic fluctuations with peak amplitudes at frequencies of 10-25 kHz. Ti is most correlated with the rotation speed and amplitudes of the n = 2, 3, and 5 modes. Potential heating mechanisms including ion cyclotron resonance damping, stochastic heating, and viscous damping are evaluated.

Acknowledgments: Work supported by US DOE grants DE-SC0018266 and DE-SC0020245, and by NSF grant PHY 1828159.

Ripudaman Singh Nirwan, West Virginia University

Title: Reconnection-Driven Electron Acceleration

Abstract: Magnetic reconnection converts the magnetic energy available in a plasma to the kinetic energy of its constituent particles. In the simplest case, it occurs between anti-parallel magnetic field lines meeting in a plane. A more general variant known as 'component reconnection' involves field lines reconnecting at an angle, giving a non-zero magnetic field component perpendicular to the plane of reconnection. This component is known as the 'guide field' and it is normalised to the reconnecting component. It controls the particle-scale dynamics of reconnection and influences the ensuing particle acceleration.

Component reconnection occurs in the Earth's magnetosphere, along with a variant known as 'electron-only' reconnection which precludes ion dynamics. West Virginia University's PHAse Space MApping (PHASMA) experiment can generate electron-only reconnection with a variable guide field. We have used this platform to study electron acceleration along the local magnetic field as a function of the guide field and found that electron acceleration is enhanced as the guide field is reduced. This occurs with the formation of non-thermal electron energy distribution functions (EEDFs) whose peak energies increase as the guide field decreases. A cross-over occurs at a guide field of 10, when the spatio-temporal production of energetic electrons in PHASMA increases dramatically. Measurements for this case reveal the production of a non-thermal, multi-component EEDF in conjunction with bulk electron heating along the local magnetic field.

Byonghoon Seo, Embry-Riddle Aeronautical University

Title: Kink-driven magnetic reconnection as the driver of a laboratory jet

Abstract: Solar jets are transient and impulsive phenomena frequently observed in the solar atmosphere. They are candidates for playing a crucial role in energizing the solar corona and driving the solar wind by transferring mass and momentum. Although observations, theories, and simulations have proposed mechanisms for solar jet generation, the fundamental question of how solar jets are initiated, heated, and accelerated at their source remains unresolved. In this talk, we introduce the experiment performed at Embry-Riddle Aeronautical University and present evidence that kink-driven magnetic reconnection serves as a mechanism for the acceleration of a laboratory filamentary blowout jet. A flux rope is formed and becomes a filamentary jet. The jet becomes unstable due to kink instability when the Kruskal-Shafranov instability criterion is met, leading to an inflow of reconnecting fields. As a result of kink-driven magnetic reconnection, ions are substantially energized, enhancing the acceleration of the jet. Based on compelling evidence observed from the laboratory, we propose that kink-driven magnetic reconnection might act as a key driver for laboratory blowout jets and is relevant to solar jets associated with kink instability and magnetic reconnection.

Ricardo Shousha, PPPL

Title: Artificial intelligence for modeling and control of complex magnetized plasma systems

Authors: R. Shousha, P. Steiner, A. Jalalvand, J. Seo, S.K. Kim, K. Erickson, A. Rothstein, H. Farre, C. Byun, M.S. Kim and E. Kolemen

Abstract: Magnetized plasma systems, such as those in fusion devices, are challenging to model and control because of their nonlinear behavior, coupled physical processes, and diagnostic limitations. Traditional physics-based methods often lack the flexibility or computational efficiency required for real-time scenarios, restricting predictive accuracy and control performance. Recent advances in artificial intelligence have allowed us to address some of these limitations. For example, real-time tokamak plasma state-estimation frameworks (e.g., RTCAKENN[1]) predict multiple plasma profiles—including electron density, temperature, pressure, current density, safety factor, ion temperature, and toroidal rotation—even under conditions of diagnostic sparsity. AI-enhanced spectroscopic techniques further enable ion profile determination from relatively simple measurements, reducing the need for costly or less robust neutral beams. Additionally, AI-based super-resolution approaches infer high-fidelity data by leveraging correlations among multiple diagnostics, offering new insights into phenomena such as ELMs and magnetic island formation. Deep reinforcement learning and other machine learning–driven strategies have also demonstrated improved control of plasma instabilities, including tearing mode avoidance[2], and the optimization of actuator configurations for ELM suppression in devices such as KSTAR and DIII-D[3]. These developments indicate that AI-based approaches, demonstrated in the context of tokamak modeling and control, may hold potential for broader application across magnetized plasma systems as well.

References:
[1] Ricardo Shousha et al 2024 Nucl. Fusion 64 026006
[2] Jaemin Seo et al.. Nature 626, 746–751 (2024)
[3] SangKyeun Kim et al Nat Commun 15, 3990 (2024)

Sanat Kumar Tiwari, Indian Institute of Technology, Jammu

Title: Kolmogorov turbulence characteristics in dusty plasma vortex flows

Abstract: Dusty plasma in laboratory experiments usually develops steady-state and complex flows due to the presence of multiple forces and continuous influx of energy. In this work, we demonstrate fully developed Kolmogorov turbulence originating from self-excited and steady-state vortex flows of charged dust fluid. Such flows originate in a three-dimensional (3D) dust cloud formed in the diffuse plasma region. Vortices of different sizes and at distant locations in the dust cloud, formed by varying discharge conditions, all demonstrate similar results, indicating the generality of the turbulent characteristics.

The flow velocities are extracted using the Particle Image Velocimetry (PIV) technique. These measurements establish the -5/3 scaling in the spatial and temporal kinetic energy spectra, a typical characteristic of 3D Kolmogorov turbulence. The results are further strengthened by obtaining the 2/3 scaling in the second-order structure function. A slight deviation in the tails of the probability distribution functions for velocity gradients reflects the signature of intermittency.

Luca Vialetto, Stanford University

Title: Low-temperature plasma chemistry for next-generation semiconductor fabrication

Abstract: Emerging technologies for micro-/nano-electronics fabrication rely on plasma processing. Engineering such devices requires a more precise process control which may be attained with a knowledge-based design of related plasma processes.

Modeling and simulation of such surface-facing process plasmas, paired with measurement data of the fabricated devices, may enable physical interpretation and guide the process design. However, despite significant increases in computational power, comprehensive multi-scale simulation remains challenging due to the complex dynamics of multi-component plasmas interacting with surfaces and critical gaps in fundamental input data for these models.

This presentation addresses the data requirements for next-generation plasma processing models, with particular focus on gas and surface kinetics. I will first present swarm analysis methods for extracting fundamental data from electron transport equation solutions and experimental measurements. Next, I will introduce a comprehensive surface kinetics model that accounts for chemisorption, physisorption, adatom diffusion, and physical sputtering mechanisms. This model, validated against experimental data, enables extraction of reaction rates for heterogeneous processes critical to fabrication outcomes.

Finally, an integrated model including plasma simulations and a data-driven surface kinetics model is presented. I will demonstrate how this hybrid approach overcomes current limitations and show its transferability to diverse applications across plasma processing and propulsion systems, establishing a foundation for more accurate and efficient plasma-based fabrication processes.

Michael Churchill, PPPL

Title: AI for connecting simulation and experiment in plasma science and fusion energy

Abstract: This presentation seeks to explore and suggest answers to the question: how can we best use AI for scientific discovery with experiment? In the first part, I will first give an in-depth overview of diffusion/flow matching AI models, including how they are being used for generative AI across many modalities including image, video, and protein structure. I will then show how these same fundamental AI techniques can be used for scientific discovery, focusing on a technique simulation-based inference (SBI). SBI enables expansive comparison of simulation models with experimental measurements, providing a principled, Bayesian methodology to determine uncertainty in physics parameters from experiments. I will discuss application to plasma physics diagnostics, both single and multiple diagnostic systems. I will also discuss how such models can form the basis of high-fidelity digital twins, forming hybrid simulation + data models for improved predictions which can be transferable to new devices.

In the second part, I will discuss emerging agentic AI tools which can aid in scientific workflows and research discovery. The development of reasoning capabilities in large language models and the ability to incorporate tool calls allows these AI models to explore and verify hypothesis, and exploit areas of promising directions. While the search space is extremely large, newer commercial AI models are using evolutionary algorithms (Google Deepmind AlphaEvolve) or other means (Microsoft Discovery) to intelligently traverse the space of possibilities. While these tools are new and developing, the principles are providing promising routes for expanding scientist capabilities for automatic parts of the scientific process.