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Physics Physics Plasma Physics

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Wednesday 26 August

Plasma Physics

Experimental Characterization of Additively Manufactured Metallic Alloys for Electric Propulsion Applications

J. Chamberlain and A. Shashurin

This work explores the sputtering of additively manufactured (AM) materials for use in gridded ion source applications. The first part of the paper uses 316L stainless steel as an example to demonstrate that additively manufactured material does not exhibit adverse sputtering behavior, such as higher sputter yield, compared with conventionally manufactured material. To this end, three additively manufactured 316L stainless steel samples were exposed to the beam of a KDC-40 electrostatic gridded ion source at three distinct energy levels of 400, 600, and 800 eV on each side of the sample for a duration of one hour. The samples were masked to create a distinct boundary between treated and untreated regions, identifiable using profilometry, and were biased to -18V for testing. Samples were then examined using a Bruker optical profilometer and further processed using the open-source software Gwyddion to evaluate the sputtering yield. The sputter yield varied in the range 0.2-2 atoms/ion for 400-800 eV ions and increased with ion energy. The measured sputtering yield was fairly consistent with predictions from analytical models developed in prior literature, while exhibiting some variations potentially due to added effects of increased temperature and oxide layers. The second part of the paper demonstrates feasibility of using an additively manufactured tungsten-rhenium grids in existing KDC-40 electrostatic gridded ion source.
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Plasma Physics

First Plasma Commissioning and Operational Highlights from India's First Spherical Tokamak at IPR

Kishore Mishra, Aditya Verma, N. Mansoori et al. (+73 more)

A compact Spherical Tokamak(ST) is commissioned at Institute for Plasma Research (IPR) to explore low aspect ratio tokamak physics and technologies that complement to the existing high aspect ratio tokamaks namely ADITYA-U and SST-1 by enabling studies on non-inductive startup, current drive in over dense plasmas, and shaped plasma physics on a low cost platform. The device, India's first spherical tokamak has completed major mechanical, magnetic, and electrical integration, and the coil system has been successfully tested with series of integrated commissioning. First plasma experiments have been carried out with a modest Ohmic system assisted by a 2.45GHz microwave system, supported by a centralized control and data acquisition system. An initial diagnostic set comprising visible imaging, spectroscopy, magnetics, and radiation monitors required for machine operation has been installed. This paper presents the integrated commissioning experiences and first plasma experiments of the newly installed machine.
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All authors Kishore Mishra, Aditya Verma, N. Mansoori, Saurabh Verma, Y. Paravastu, M. S. Khan, Arvind Kumar, S. G. Thatipamula, Vishal Verma, M Sheetal, Mohit, U. Thaker, Ayush, Jignesh Patel, Praveenlal, Jagabandhu Kumar, F. S. Pathan, S. Ranjithkumar, S. Sam, Prasada Rao P., A. Jaiswal, S. Jha, Neelam Ramaiya, Utsav Rajvanshi, Santosh Pandya, K. Tahaliyani, S. Purohit, Suraj Gupta, Kiran Patel, Suman Aich, D. Kumawat, Deepak Kumar, Saurav Kumar, Rahul Kumar, Vismaysinh Raulji, Pramila, Praveena Kumari, Minsha Shah, Arun Prakash, Narendra Bhupesh, Amit K. Singh, V. Menon, Deepti Sharma, A. Kundu, G. K. Rajan, Prakash Parmar, Ankit Kumar, Vishnu Patel, Imran Mansuri, M Bhandarkar, H. Chudasma, Atish Sharma, Kirit Patel, H Masand, Prem Kumar, Parmesh Kumar, S Kannaujiya, Pramod Parmar, Arvind L. Thakur, C. G. Virani, Ankit Kumar, K. K. Ambulkar, Vilas Chaudhari, C. Danani, Y. S. S. Srinivas, S. Nair, K. Mahajan, R. Rajpal, M. B. Chowdhury, Manoj Kumar, S. K. Pathak, P. K. Sharma, Z. Khan, E. Rajendrakumar, J. Ghosh, Team ST

Plasma Physics

Machine learning methods for modelling local, linear gyrokinetic simulations of MAST-U pedestal turbulence

Anna Niemelä, Daniel Jordan, Aaro Järvinen et al. (+8 more)

Gyrokinetic (GK) stability strongly influences the performance of high-confinement-mode pedestals in spherical tokamak plasmas. High-fidelity gyrokinetic codes such as GENE can model microinstability-driven transport, but the computational cost limits their routine use in integrated pedestal modeling workflows. Instead, present workflows often rely on reduced transport assumptions, such as the ballooning-critical pedestal model used in EPED. This work investigates machine-learning surrogate models for local linear gyrokinetic simulations in a MAST-U-relevant pedestal parameter space, with the aim of providing faster gyrokinetic-based inputs to reduced pedestal models. A sampling workflow is developed in which pedestal profile parameters are varied within experimentally motivated bounds and used to generate physically self-consistent Grad-Shafranov equilibria. This reduces the dimensionality of the data-generation problem compared with sampling local gyrokinetic inputs directly, while maintaining physically plausible combinations of plasma profiles, geometry, and local stability parameters. The surrogate models are trained to predict linear growth rates, real frequencies, and diffusivity-ratio transport fingerprints from local linear GENE simulations. A multi-head multilayer perceptron accurately reproduces the growth rate, while the diffusivity ratios and real frequency exhibit more clustered, regime-dependent behavior. A multi-head classification-regression model using frequency-based regime classes reduces the mean absolute error for these clustered targets and better captures sharp transitions associated with changes in the underlying instability regime, although errors near mode-transition regions remain a limitation.
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All authors Anna Niemelä, Daniel Jordan, Aaro Järvinen, Amanda Bruncrona, Adam Kit, Lorenzo Frassinetti, David Hatch, Leonhard Leppin, Samuli Saarelma, the MAST Upgrade team, EUROfusion Tokamak Exploitation team

Plasma Physics

Ion-acoustic eigenmodes in a helical magnetic mirror

Ivan Chernoshtanov

Plasma rotation together with corrugation of magnetic field can result in coupling acoustic waves with different azimuthal wavenumbers and formation of eigenmodes with discrete frequency spectrum and zero longitudinal group velocity in a helical magnetic mirror. Such eigenmodes can be destabilized by plasma rotation as well as resonant interaction with trapped ions. Equations describing these waves in the linear approximation are derived and results of numerical solving the equations are discussed. Probably these eigenmodes may drive anomalous ions scattering which is needed for effective suppressing flow of rarefied plasma through a helical mirror.
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Plasma Physics

A generalized energy-consistent finite difference scheme for 10-moment magnetohydrodynamics

Keita Akutagawa, Shinsuke Imada and Munehito Shoda

Pressure anisotropy and off-diagonal pressure stresses are ubiquitous and play important roles in collisionless/weakly collisional plasmas. The Chew-Goldberger-Low (CGL) MHD model is often used; however, it can lose hyperbolicity when the pressure anisotropy or plasma beta becomes large, making it hard to develop approximate Riemann solvers. An alternative approach is to use the 10-moment MHD equations, but their eigenmode analysis is also difficult, which similarly hinders the development of less-diffusive Riemann solvers. This paper presents a new energy-consistent finite difference scheme for 10-moment MHD designed to operate over a broad range of plasma beta. The proposed scheme extends the 10-moment MHD model using the energy-consistent finite-difference approach developed for conventional MHD. Nonlinear filtering is applied to all six independent components of the pressure tensor, and the kinetic and magnetic energies dissipated by the filtering are explicitly transferred to the diagonal pressure components under an equipartition assumption to maintain consistency with the total energy balance. The proposed scheme is validated against seven test problems in the isotropic limit, the gyrotropic limit, and without isotropization/gyrotropization. The results demonstrate the expected spatial convergence and total energy behavior, reproduce the linear growth rate, and yield pressure tensor structures qualitatively consistent with theoretical expectations and previous simulations, spanning plasma beta values from $10^{-10}$ to $10^{10}$. The proposed scheme provides a promising framework for large-scale simulations of collisionless plasmas across widely separated plasma beta regimes and opens a path toward applications such as solar wind turbulence and plasmoid-mediated reconnection.
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Tuesday 25 August

Plasma Physics

Physics-Informed Neural Operator Surrogate for 2D Magnetohydrodynamic Reconnection

Kushaal Kumar Pothula and Arunav Kumar

Direct numerical simulation of magnetic reconnection is limited by the scale separation of resistive magnetohydrodynamics. At large Lundquist numbers $S$ the current layer thins as $S^{-1/2}$, forcing fine grids and short time steps that make parameter scans prohibitively expensive. Deep learning neural operators offer an alternative by learning the map between function spaces rather than individual solutions, so that a single trained model returns the state for any parameter and time at inference cost. We have developed a Fourier Neural Operator (FNO) based Physics-Informed Neural Operator (PINO) surrogate for two-dimensional compressible, viscous, resistive reconnection in a wall bounded domain. We condition on the initial state, the Lundquist number, and a continuous query time. Predicting the magnetic flux function makes $\grad\!\cdot\!\bB=0$ exact, direct time queries remove autoregressive error accumulation, and parity-aware spectral differentiation matches the wall treatment of the reference solver. Trained across $10^{3}\le S\le2\times10^{5}$ with two values withheld, the surrogate recovers density, pressure, and guide field to better than $0.2\%$, velocity to $3.2$ to $3.9\%$, the flux function to $1.0\%$, and the spectral current density to $7.5\%$. It resolves the thin, narrow current sheet, Alfvénic jets, and spectral resolution beyond mode cutoff. Our surrogate reproduces the layer-averaged reconnection rate to within $3\%$ through $S=1.1\times10^{4}$, recovering a reconnection time exponent of $0.497$ consistent with Sweet-Parker scaling. When queried zero-shot on the $2049^{2}$ solver mesh, a full trajectory run is on the order of seconds on one GPU against several hours for the DNS, over two orders of magnitude faster, establishing learned operators as a practical route to surveying reconnection across parameter space.
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Plasma Physics · Cross-listed from physics.acc-ph

High-charge collimated and energy-selected laser-driven MeV electron beams produced by magnetic selection

I. Cohen, I. Slabu, Q. Peysson et al. (+16 more)

We have developed a compact passive energy-selector for MeV-range electrons produced by irradiating solid targets by ultra-intense short-pulse lasers. The device allows for generating electron beams with a variable energy spread over a broad range of energies, from tens of keV to tens of MeV. Here we have demonstrated its use by producing electrons from solid targets in the MeV range and with a ~10% bandwidth, thereby compensating the intrinsic broadband nature of the electrons produced from such source. Coupled with a pulsed magnetic field to further compensate the intrinsic large divergence of this source, it allows to produce a highly-collimated beam of narrow-band and ultra-fast electrons, suitable for a wide range of applications, e.g. radiation therapy or time-resolved electron probing.
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All authors I. Cohen, I. Slabu, Q. Peysson, S. Dorard, Y. Abe, J. Béard, T. Moraine, S.N. Chen, A. Chessa, K.Iida, P. Kempski, Y. Kuramitsu, H. Kusano, F. Nikaido, M. Ruszkowski, K. Sakai, N. Tamaki, O. Tesileanu, J. Fuchs

Plasma Physics

Physics Attention Transformer Surrogate for Rapid Vertical Instability Growth Rate Prediction: Alcator C-Mod to SPARC

Arunav Kumar, Cesar Clauser, Theodore Golfinopoulos et al. (+5 more)

In this work, we investigate rapid prediction of the dominant $n{=}0$ vertical instability growth rate in C-Mod and SPARC equilibria, where nonrigid free boundary response models are too slow for control cycle use. Using a Physics Attention Transformer trained on MEQ-FGE-L labels, we predict both the scalar growth rate and the associated two dimensional perturbed toroidal current density. We find mean absolute errors of 5.4~s$^{-1}$ on held out C-Mod equilibria and 12.7~s$^{-1}$ on synthetic SPARC cases, with spatial eigenfunction errors near 5%. We also compared PAT with operator based ML models : FNO2D and DeepONet, where we found PAT predicts a much lower normalised growth rate error and improved spatial reconstruction. These results indicate that PAT can reproduce MEQ-FGE-L outputs at control relevant latency and could support future studies of growth rate headroom monitoring and proximity aware shape control.
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All authors Arunav Kumar, Cesar Clauser, Theodore Golfinopoulos, Cristina Rea, Francesco Capersene, Dan Boyer, SPARC Team, Alcator C-Mod Team

Plasma Physics · Cross-listed from astro-ph.SR

Calculation of Field Line Slippage Rates in Coronal Simulations

Valentin Aslanyan, David MacTaggart, Roger B. Scott et al. (+6 more)

We present the Universal Slippage calculator (USlip), an extension of the Universal Fieldline Tracer (UFiT), that computes magnetic field line slippage rates from an input magnetic field defined on a structured grid. The slippage rate provides a local, physically grounded diagnostic of non-ideal evolution, directly quantifying departures from ideal frozen-in motion. We outline the theoretical formulation and describe an efficient numerical implementation. The method is validated against analytical solutions and applied to simulations using three coronal codes treating varying spatial scales, all of which are standard inputs for USlip. In all the examples considered, the slippage rate not only identifies where magnetic connectivity changes occur, but also accurately reproduces the observed direction of field-line slippage. The consistency of the results across analytical tests and multiple simulation platforms demonstrates that USlip is a robust and versatile tool for diagnosing three-dimensional reconnection in dynamically evolving systems.
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All authors Valentin Aslanyan, David MacTaggart, Roger B. Scott, Chloe P. Wilkins, David I. Pontin, Anthony R. Yeates, Peter F. Wyper, Karen A. Meyer, Spiro K. Antiochos

Plasma Physics

Spatio-Temporal Synchronization of Counter-Propagating Femtosecond Pulses

Tamir Cohen, Moshe Fraenkel and Ishay Pomerantz

Generating intense x-ray radiation via inverse-Compton scattering and exploring the strong-field regime of QED, require precise spatio-temporal synchronization of tightly focused counter-propagating intense laser pulses. We present a protocol for establishing spatio-temporal synchronization in this geometry that combines microscope-based target positioning, wavefront-sensor-assisted alignment of off-axis parabolic mirrors, and a high-resolution temporal delay scan based on interference. We observed an interference window of 72 fs in good agreement with the expected autocorrelation width. The accuracy levels in space and time of using this protocol are discussed.
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Plasma Physics

Anomalous Electric Fields in Earth's Turbulent Magnetosheath: Insights From 3D Hybrid Simulations

Jeffersson A. Agudelo Rueda, Julia E. Stawarz, Luca Franci et al. (+3 more)

In both collisional and collisionless plasmas the presence of a broad range of electromagnetic and plasma fluctuations provides anomalous electric fields that can be important for the dynamical evolution of the system as it is the case of magnetic reconnection, plasma turbulence and dynamo theory. In the context of plasma turbulence at scales larger than the ion's inertial length, the plasma satisfies the frozen-in condition, and the anomalous electric fields are produced by correlations between turbulent velocity and magnetic fields. Conversely, for collisionless plasmas and at kinetic scales, the total electric field has additional contributions that arise from kinetic phenomena, namely, charge separation, ambipolar electric fields and electron inertia, and each of these terms presents an anomalous counterpart. In this work we characterize the anomalous electric fields. We present a framework that can explain partial balance between the anomalous resistivity and anomalous transport, and we use it to study anomalous electric fields at kinetic scales. We establish how the different contributions to the anomalous electric field couple to the large-scale electric fields and show that the anomalous terms act back-reacting on magnetic-field organization and they may contribute to effective turbulent magnetic diffusion or shielding. Finally, we test two Sub-Grid-Scale models including anisotropic transport coefficients and show that although these models partially recover the spectral information, the phase coherence is not entirely recovered by these models suggesting a more complex non-linear contribution of the anomalous terms to the resolved scales.
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All authors Jeffersson A. Agudelo Rueda, Julia E. Stawarz, Luca Franci, Nobumitsu Yokoi, Camille Granier, Silvio S. Cerri

Plasma Physics

First-Principles Simulation of Electron-Ion Collisional Transport in Magnetized and Unmagnetized Plasmas

Keheng Zhu, Jian Liu, Chaozhou Mou et al. (+2 more)

Accurate electron-ion collision models are central to predicting transport in fusion and space plasmas, yet most practical formulations rely on binary-collision assumptions and impact-parameter cutoffs whose quantitative accuracy is difficult to assess directly. We develop a first-principles simulation framework for collisional transport by solving the Newton-Lorentz equations for test electrons in the many-body electric field of a Debye-screened ion background, without imposing binary-collision closures or artificial lower cutoffs. The method combines explicit force summation within a Debye sphere, a volume-preserving particle pusher, and adaptive time stepping, enabling stable and scalable simulations in both unmagnetized and magnetized plasmas. Using simulation-based measures of momentum relaxation and cross-field diffusion, we recover the classical scalings for the electron-ion collision frequency and perpendicular diffusion coefficient, namely $\nu_{ei} \propto v_{th}^{-3}$ and $D_\perp \propto B^{-2}$. Within the parameter range studied, both simulated coefficients are lower than their corresponding classical estimates by approximately 15-25%. These regime-specific benchmark results indicate that classical transport theory captures the leading scaling behavior, but that the corresponding quantitative prefactors can remain sensitive to many-body and near-field effects in the simulated regime. The framework therefore provides a computational benchmark for testing and improving reduced collision operators and transport models.
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All authors Keheng Zhu, Jian Liu, Chaozhou Mou, Senran Lin, Wei Zhang

Plasma Physics

An Inverse Grad-Shafranov Neural Network Approach to Tokamak Magnetic Control

Allen M. Wang, Adriano Mele, Cosmas Heiß et al. (+12 more)

A new approach to tokamak magnetic control enabling high-precision plasma shaping and novel real-time adaptability is experimentally demonstrated on the Tokamak a Configuration Variable (TCV). The method is motivated by the insight that, under appropriate assumptions, a real-time inverse Grad-Shafranov solver approximates an optimal control policy for plasma boundary regulation. Building on this, a control architecture is developed in which classical controllers enforce operational constraints while a fast surrogate model provides a real-time inverse mapping from the desired plasma boundary to Poloidal Field Coil currents. Experimental results on TCV demonstrate improved plasma shaping with respect to the standard discharge preparation procedure — albeit without explicit real-time shape feedback — while enabling flexible response to asynchronous events. It is shown that a single network provides satisfactory performance across a range of plasma magnetic configurations. Real-time adaptivity is demonstrated in simulation, and partially in experiment, through adaptive strike point motion and early termination in response to a real-time trigger. These results suggest a viable path toward magnetic control architectures that reduce reliance on dense diagnostic coverage while maintaining high-accuracy plasma shaping, with potential relevance for future fusion power plant operation.
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All authors Allen M. Wang, Adriano Mele, Cosmas Heiß, Cristian Galperti, Zander Keith, Alessandro Pau, Antoine Merle, Olivier Sauter, Daniel Gonzalez Castiñeiras, Francesco Carpanese, Federico Felici, Mark Dan Boyer, Cristina Rea, TCV Team, EUROfusion Tokamak Exploitation Team

Monday 24 August

Plasma Physics · Cross-listed from physics.comp-ph

Macroparticles with different weights relax to different temperatures in Particle-In-Cell simulations

Remi Lehe, Arianna Formenti, Justin R. Angus et al. (+1 more)

A distinctive feature of Particle-In-Cell (PIC) simulations is the use of macroparticles, each representing many physical particles. The associated macroparticle weight can vary from one species to another, or even from one macroparticle to another. Here we show that, when macroparticles have different weights, the plasma evolves toward an unphysical thermal equilibrium in which the temperatures are unequal: lower-weight macroparticles reach a higher temperature than physically expected, and higher-weight macroparticles a lower one. We show that this unphysical equilibrium is difficult to avoid, but that reaching it takes time, and that the associated timescale depends on the effective collisionality of the PIC algorithm. We derive an equation that predicts the full time evolution of the temperatures, in good agreement with PIC simulations, and use it to identify strategies to delay the establishment of this unphysical thermal equilibrium.
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All authors Remi Lehe, Arianna Formenti, Justin R. Angus, Jean-Luc Vay

Plasma Physics

Helical jets driven by a ring of laser irradiation

Kian Orr, Brandon K. Russell, Kirill Lezhnin et al. (+5 more)

Plasma jets are formed in various astrophysical systems as plasma is rapidly ejected from a source, with a subset of these jets being magnetized and having a helical structure. Here, we demonstrate that helical jets may be formed using a ring of laser pulses that arrive on planar foils sequentially with increasing energy. The formation of the jets and their properties, including kinetic helicity, are studied through a set of three-dimensional magneto-hydrodynamics simulations with conditions informed by the parameters of the OMEGA laser facility. We find that jets with a higher degree of helicity may be generated under realistic experimental conditions when compared to a uniform jet. Synthetic x-ray and Thomson scattering diagnostics computed from simulated data demonstrate that the helical jet provides a unique fingerprint in both its morphology and plasma parameters. This laboratory helical jet platform may allow for controlled experimental study of the dynamics of helical plasma structures and, through interaction with other jets or targets, can allow for studies of shear-driven turbulence and mixing relevant to interactions between astrophysical jets and ambient clouds or crosswind.
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All authors Kian Orr, Brandon K. Russell, Kirill Lezhnin, Yang Zhang, Geoffrey Pomraning, Petros Tzeferacos, Hantao Ji, Lan Gao

Plasma Physics

AI Surrogate Modeling for Real-Time Tokamak Equilibrium Prediction: Benchmarking Neural Architectures and Validation on EXL-50U

Guoyang Shi, Zitong Zhang, Siqi Ding et al. (+5 more)

Fast and reliable plasma equilibrium prediction is essential for real-time tokamak operation and control, but conventional Grad-Shafranov (GS) solvers are often too costly for real-time deployment. We develop an AI surrogate framework and benchmark five architectures (MLP, CNN, FNO, Transformer, and KAN) on a numerical GS database with 100,000 IID and 10,000 OOD samples. Under a unified protocol, we evaluate accuracy, inference efficiency, model scaling, and robustness. We also establish device-level validation on the EXL-50U tokamak by linking numerical GS solutions, surrogate predictions, and the standard Shape Editor reference to assess simulation-to-device consistency. The surrogates achieve errors of $10^{-3}$-$10^{-2}$ relative to GS solutions, while the GS-to-device discrepancy remains at $10^{-3}$. Transformer gives the best IID accuracy, whereas CNN offers the best balance of accuracy, robustness, and speed, reaching 0.7 ms TensorRT latency. On unseen plasma geometries and parameter regimes, CNN and FNO show the strongest extrapolation stability, with 4%-5% relative $L_2$ error, while models with weaker inductive biases degrade more substantially. Scaling data and model capacity improves interpolation but not necessarily extrapolation, revealing a trade-off between capacity and OOD generalization. Overall, this work provides a systematic, device-consistent benchmark for AI-based GS prediction and practical guidance for selecting reliable surrogates for real-time plasma control and fusion applications.
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All authors Guoyang Shi, Zitong Zhang, Siqi Ding, Jianguo Chen, Yapeng Zhang, Jiayi Zhi, Hanyue Zhao, Tianyuan Liu

Plasma Physics · Cross-listed from physics.flu-dyn

Lagrangian Curvature Statistics from Gaussian Subensembles in Turbulent Flows

Yasmin Hengster, Johannes Bosbach, Daniel Schanz et al. (+2 more)

A salient feature of fully turbulent flows far from onset is the intermittent occurrence of extreme fluctuations at small spatial and temporal scales. These have a qualitative and quantitative effect on the instantaneous curvature of a tracer particle trajectory as an intrinsically multi-scale observable. Here, we provide a complete statistical description of the curvature of tracer particle trajectories in turbulent flows that includes and quantifies intermittency effects. We derive an exact expression and a closed-form approximation for the curvature probability density function, both agree well with data obtained from laboratory experiments of different types of turbulent flows, and quantify the generic behavior of the system. The method can be extended to more complex systems such as plasma turbulence.
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All authors Yasmin Hengster, Johannes Bosbach, Daniel Schanz, Andreas Schröder, Moritz Linkmann

Plasma Physics · Cross-listed from quant-ph

Efficient Quantum Simulation of Linearized Vlasov–Poisson Dynamics Using Trotter and THRIFT Hamiltonian Simulation Methods

Kartick Paul, Rahul V, S. Aravinda et al. (+1 more)

The Vlasov–Poisson system provides the fundamental kinetic description of plasma and plays a central role in understanding collective phenomena such as Landau damping and wave–particle interactions. Efficient numerical simulation of these dynamics remains challenging because of the high dimensionality of phase space. In this work, we studied magnetized and non-magnetized plasma using a quantum simulation framework for the linearized Vlasov-Poisson equation by reformulating the discretized system as a Hermitian Hamiltonian suitable for gate-based quantum computation. The time evolution is implemented using first, second and fourth-order Trotter–Suzuki product formulas and the recently proposed Time-Resolved Interaction Framework (THRIFT). The performance of the different simulation methods is systematically evaluated through electric field evolution, state fidelity, convergence behavior, energy conservation, entanglement entropy and quantum resource requirements, including circuit depth and two-qubit gate complexity, for both magnetized and non-magnetized plasma models. To further reduce finite time step errors without increasing circuit depth, Richardson extrapolation is incorporated as a error-mitigation technique. The results provide a comprehensive comparison of Trotter and THRIFT approaches and establish practical guidelines for accurate and resource-efficient quantum simulation of plasma dynamics on gate-based quantum computers.
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All authors Kartick Paul, Rahul V, S. Aravinda, Reetesh K. Gangwar

Plasma Physics

Areal-time disruption prediction and mitigation system for the EXL-50U spherical torus

J.P.Zhou, S.F.Liu, J.Q.Cai et al. (+10 more)

This work presents a real-time disruption prediction and mitigation system developed for high-current operations in the EXL-50U Spherical Torus. By leveraging Reflective Memory (RFM) technology, the system establishes a low-latency real-time data path, creating a fully integrated pipeline that synchronizes multi-channel diagnostic acquisition, online preprocessing, real-time inference, and Massive Gas Injection (MGI) triggering. At its core, a lightweight prediction model based on a Temporal Convolutional Network (TCN) with a channel attention mechanism extracts disruption precursor features while adaptively weighting the importance of different diagnostic channels. {Tested across discharges \#14036–\#14790, the system achieves a true positive rate of 82.4% and a false positive rate of 16.5%, with end-to-end latency below $1~\mathrm{ms}$ in online operation.} Mitigation experiments further show that the MGI system can supply the required gas inventory and trigger a rapid post-injection plasma response, supporting the operational requirements of EXL-50U and providing engineering guidance for future devices such as EHL-2. These results confirm the engineering feasibility of integrated real-time disruption control on EXL-50U, offering a robust basis for future research in higher-parameter fusion devices.
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All authors J.P.Zhou, S.F.Liu, J.Q.Cai, H.Y.Zhao, J.Li, Y.P.Zhang, D.Guo, C.Wu, A.Wang, H.Y.Li, C.Zhang, Z.Y.Chen, Y.J.Shi

Plasma Physics

On the feasibility of model-based feedback control of vertical instability growth rate using out-vessel coils in ARC-like scenarios

Arunav Kumar, Cesar Clauser, Theodore Golfinopoulos et al. (+1 more)

In this work, we propose a model-based feedback controller that regulates the vertical instability growth rate ($\gamma_{gr}$) of a high-elongation, double-null tokamak directly, using only out-vessel poloidal field (PF) coils. High elongation raises the achievable plasma current and fusion performance but makes the plasma vertically unstable, and in a fusion power plant the in-vessel coils that present devices rely on for stabilization may be absent, leaving only distant out-vessel circuits. The controller couples a machine learning surrogate of non-rigid, profile agnostic vertical instability metric to a constrained quadratic program: the surrogate supplies real-time $\gamma_{gr}$ estimates and, via automatic differentiation, the actuator sensitivities, while the program allocates coil voltages to track a target growth rate, maintain double-null divertor balance, and respect electromechanical limits. We tested this method on the ARC~V3A power plant design configuration across 24 closed-loop simulations spanning equilibrium variations, actuator degradations, and transient disturbances. We achieved full or marginal success in 83% of these cases (full in 50%, marginal in a further 33%) and lose control in the remaining 17%; the failures map the boundary of out-vessel controllability (occurring at the highest growth rates) and under actuator limits. The controller does not regulate boundary shape explicitly: separatrix geometry follows indirectly from growth rate and flux balance control and would require a separate shape control layer for sustained scenario evolution.
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All authors Arunav Kumar, Cesar Clauser, Theodore Golfinopoulos, Jon C. Hillesheim

Sunday 23 August

Plasma Physics

Early-Time Reshaping of Laser-Induced Plasma Profiles

Ivan Ostrovsky, Gilad Hurvitz, Soumitra Hazra et al. (+1 more)

Laser-induced plasmas are primarily characterized by their temporal density decay. Using time-resolved transverse optical diffractometry, we reveal their concurrent spatial evolution, demonstrating pronounced broadening and flattening during the first 200 ps following ionization. This non-self-similar evolution arises from the local density dependence of electron-ion recombination, without particle transport. Exploiting the continuum of initial densities within a single plasma disc, we experimentally reconstruct an effective, time-dependent local recombination law over a broad density range. Applied locally to independently measured initial plasma profiles, this kinetic map quantitatively predicts their subsequent evolution. These results are relevant to transient diffractive optics, plasma-based optical elements and waveguides, and the development of laser-induced plasmas as platforms for gas-phase THz plasmonics.
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All authors Ivan Ostrovsky, Gilad Hurvitz, Soumitra Hazra, Sharly Fleischer

Plasma Physics

Interpretable statistical feature engineering for early disruption prediction in the short pulse ADITYA tokamak

Jyoti Agarwal, Kavit Patel, Bhaskar Chaudhury et al. (+3 more)

Reliable early disruption prediction is critical for the safe operation and real-time control of tokamaks. However, machine learning based prediction frameworks have predominantly targeted medium and long pulse devices, with comparatively limited attention given to short pulse tokamaks where available warning time is inherently constrained. In this work, an interpretable machine learning framework is developed for feature engineering and early prediction of disruptions in the ADITYA using the initial plasma evolution information, prior to the activation of the negative converter of the ohmic transformer power supply. Statistical descriptors comprising the mean, variance, skewness, kurtosis and wavelet energy entropy are extracted from routinely available plasma diagnostics over different operation time windows. Decision tree based feature selection is employed to identify physically meaningful disruption precursors and to reduce feature dimensionality. These selected features are used to train a random forest classifier. The proposed framework achieves stable predictive performance across different analysis windows, with a maximum ROC-AUC of 0.87 for 0-35 ms and 0-40 ms windows. Comparable and in some cases improved, performance is obtained using the reduced feature set, demonstrating that the selected statistical descriptors retain the essential information required for disruption prediction. The proposed methodology provides an interpretable and computationally efficient framework for real time disruption prediction in short pulse tokamaks and establishes that carefully engineered statistical descriptors can effectively replace raw time series inputs for early disruption prediction, thereby offering a practical pathway toward real time plasma control in short pulse tokamaks similar to ADITYA and ADITYA-U.
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All authors Jyoti Agarwal, Kavit Patel, Bhaskar Chaudhury, Abhishek Sharma, Shrichand Jakhar, Manika Sharma

Plasma Physics · Cross-listed from physics.acc-ph

Stationary electron vortex states in a plasma bubble field

Hui-Dong Huang, Qi Meng, Zhi-Bin Wang et al. (+3 more)

Plasma wakefield accelerators (PWFAs) offer accelerating gradients of 10-100~GV/m and relativistically propagating plasma bubbles capable of confining charged particles. We study the stationary states of a vortex electron at the bubble center by solving the corresponding quasi-relativistic Schrödinger equation. Analytical solutions are obtained with Laguerre-Gaussian transverse modes and Hermite-Gaussian longitudinal envelopes. Comparing the resulting beam parameters with experimentally accessible vortex-electron bundles, we find that the transverse beam waist supported by the plasma bubble is comparable to that achieved by current electron-optical techniques. The longitudinal confinement further provides a favorable parameter regime for stable injection. Our results indicate the feasibility of maintaining localized vortex-electron states in a plasma-bubble wakefield and provide an analytical starting point for investigating their subsequent acceleration and stability.
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All authors Hui-Dong Huang, Qi Meng, Zhi-Bin Wang, Liang Lu, Jian Chen, Li-Ping Zou

Plasma Physics

Wavefront-Guided Electron Injection for Direct Laser Acceleration in Relativistic Laser-Driven Plasma Channel

Heng Wang, Liang Sheng, Long Zeng et al. (+2 more)

We investigate electron injection into direct laser acceleration (DLA) in relativistic laser-driven plasma channels using particle-in-cell simulations. We identify and characterize a wavefront-guided injection mechanism, in which electrons are continuously fed into the plasma channel through the density pile-up layer at the laser-pulse front. Phase-space analysis reveals a localized injectable region within the pile-up layer, indicating that only a selected subset of electrons satisfies the conditions required for the subsequent direct laser acceleration. This mechanism provides a physical interpretation for the high-charge capability of DLA by explaining how electrons are continuously supplied to the accelerating channel. Beyond this continuous supply process, the injection dynamics are further modulated by the periodic variation of the carrier phase at the laser-pulse front. The spatial locations of injected electrons are found to be closely associated with magnetic-island structures formed under laser-phase modulation, suggesting that the laser wavefront not only supplies electrons but also organizes their entry into the accelerating channel. These findings advance the physical understanding of energetic-electron generation in relativistic laser-driven subcritical-density plasma channels and are relevant to the development of compact DLA-based particle and radiation sources.
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All authors Heng Wang, Liang Sheng, Long Zeng, Yang Li, Zheng Gong

Plasma Physics

Plasmon-polaritons in a rarefied nonrelativistic neutron gas

P.O. Kazinski and A.M. Trushchuk

The electromagnetic properties of a dilute unpolarized nonrelativistic neutron gas are described in the case when neutron-by-neutron scattering is negligible. The Gaussian (Maxwell-Boltzmann) and Fermi-Dirac one-particle density matrices for the neutron gas are considered, the typical space scale of variations of these density matrices being assumed to be much larger than the the typical space scale of variations of the electromagnetic field. The Green functions for the static effective Maxwell equations are obtained. The parameters of a nonequilibrium neutron gas are found where this gas possesses a ferromagnetic instability. The analog of Friedel oscillations is described. The properties of plasmon-polaritons in the neutron gas are revealed. It turns out that the dispersion law of longitudinal and transverse plasmon-polaritons has an infinite number of branches at a given momentum. The region of parameters where the plasmon-polaritons can be regarded as quasiparticles is found. The plasmon-polaritons on a Gaussian wave packet of a single electron are described. Their dispersion law proves to have an infinite number of branches at a given momentum. It is shown that there exist stable longitudinal plasmon-polaritons even on a single electron.
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Saturday 22 August

Plasma Physics

Modified Kalman Filtering Derived from Non-Maxwellian Distribution Functions in Open Systems

Olivier Izacard

Kalman filtering (KF) recursively infers plasma quantities, represented by a state, from noisy diagnostics while propagating uncertainty in the inferred state separately from diagnostic noise. For linear dynamical and measurement models with Gaussian probability density functions (PDFs), the state mean and covariance provide the KF description. We modify this KF for open plasmas with particle and energy sources by extending the physical state from Maxwellian variables to retained NMDF coordinates, whose evolution follows a projection of the nonlinear Landau-Fokker-Planck equation. The same NMDF state is propagated through a fixed diagnostic response to obtain the corresponding measurement PDF. Because a non-Gaussian likelihood can drive the posterior outside the Gaussian family, the mean-covariance representation is extended to a finite moment closure whose coordinates are related to the retained moments through their Jacobian. The recursive prediction-correction structure is preserved, recovering conventional KF results for linear models with Gaussian PDFs. As a proof of concept, we use seven published non-Gaussian Alcator C-Mod Langmuir-probe current PDFs. For each target PDF, NMDF response parameters are calibrated from the other probe PDFs and frozen; this excluded target tests independent prediction. This test shows that different plasma regions require different NMDF structures, instead of the standard assumption of Maxwellian velocity distributions across all regimes and locations. Because the published measurement PDFs do not retain time ordering, this proof of concept does not yet test recursive uncertainty dynamics. Implementing the projected Landau-Fokker-Planck prediction with time-resolved diagnostics is the next step toward full validation of the modified KF.
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Plasma Physics · Cross-listed from astro-ph.HE

Pair Discharges and Radio Emission from Millisecond-Pulsar and White-Dwarf Magnetospheres

Tuomo Salmi and Joonas Nättilä

Coherent radio emission is observed from compact astrophysical objects with relatively weak magnetic fields, including millisecond pulsars and white dwarfs, the latter being proposed as possible sources of long-period radio transients. In such environments, the standard pair discharge mechanism—driven by curvature radiation and one-photon pair production—can fail because the low magnetic field strength suppresses photon conversion. We analyze a discharge mechanism that operates efficiently in weak-field magnetospheres, including two-vertex quantum electrodynamic processes: inverse Compton up-scattering of background photons followed by either two-photon or one-photon pair creation depending on the seed photon temperature. Using first-principles radiative particle-in-cell simulations incorporating exact QED cross sections, we demonstrate that these mechanisms robustly generate pair cascades in millisecond-pulsar magnetospheres and in hot white-dwarf environments. The resulting system exhibits limit-cycle behavior and generates electromagnetic field fluctuations capable of producing coherent radio emission, providing a natural explanation for radio activity in low-field compact objects.
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Plasma Physics · Cross-listed from astro-ph.HE

Pair Discharges and Radio Emission from Pulsar Magnetospheres

Joonas Nättilä and Tuomo Salmi

Radio pulsars can power their coherent radio emission through intermittent plasma discharges in magnetospheric gaps. The nonlinear coupling between particle acceleration, quantum electrodynamic (QED) processes, and electric field screening remains difficult to model self-consistently. We present an analytical concurrency model and first-principles particle-in-cell (PIC) simulations of polar cap discharges. The model predicts limit-cycle behavior where the electric field and plasma density oscillate with a frequency set by the local plasma frequency, modified by the plasma inertia. One-dimensional simulations with exact QED rates and realistic plasma parameters validate these predictions. The discharges generate pair multiplicities up to $M_\pm \sim 10^4$ and excite electric field oscillations with spectra consistent with pulsar radio microstructure. These results provide a theoretical framework connecting microphysical gap dynamics to macroscopic observables.
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Plasma Physics

State-Space Model-Enabled Reinforcement Learning for Magnetic Configuration Controlon EXL-50U

Pei Guo, Zhengyuan Chen, Jianguo Chen et al. (+17 more)

Accurate feedback control of the plasma current ($I_p$) and centroid position $(R_c,Z_c)$ is essential for the stable operation of spherical torus (ST) plasmas. Conventional proportional-integral-derivative (PID) controllers require extensive manual tuning and struggle with the fast, strongly coupled dynamics that arise as plasma performance improves. Reinforcement learning (RL) has recently emerged as a promising alternative to such complex magnetic control problems, yet its practical deployment on ST devices remains challenging. This paper presents a practical RL controller for the EXL-50U ST, trained within a rigid RZIP state-space model (SSM) that enables efficient offline policy learning. A lightweight plasma position reconstructor is developed to estimate $(R_c,Z_c)$ from magnetic probe signals within the real-time control cycle. The trained policy is seamlessly deployed on the EXL-50U plasma control system, achieving stable regulation of $I_p$ and $(R_c,Z_c)$ and sustaining discharges up to 650 ms under RL control. These results demonstrate the feasibility and practical potential of model-informed RL for magnetic configuration control in ST devices, offering a promising direction beyond conventional PID-based schemes.
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All authors Pei Guo, Zhengyuan Chen, Jianguo Chen, Xuanhe Wang, Guoyang Shi, Siqi Ding, Yapeng Zhang, Lei Xing, Yong Liu, Xiang Gu, Tiantian Sun, Xiuchun Lun, Jia Li, Zhengxiong Wang, Huasheng Xie, Hanyue Zhao, Yuejiang Shi, Xianming Song, Tianyuan Liu, EXL-50U Team

Plasma Physics · Cross-listed from math.NA

Wasserstein Moment Nudging for Vlasov-Poisson Data Assimilation

Liyao Lyu, Xinyue Yu, David Schneidinger et al. (+1 more)

We introduce a continuous data assimilation method for particle-in-cell simulations of the Vlasov-Poisson equation when only hydrodynamic moments are observed. The forecast state is an empirical measure on phase space, whereas the observed fields (density, bulk velocity, and temperature) constrain only a few velocity moments and leave the velocity-space shape of the distribution undetermined. We construct the moment feedback as a Wasserstein gradient flow of a moment-mismatch functional over phase-space measures. The resulting drift acts directly on particle positions and velocities, couples the density, momentum, and energy residuals through a single variational structure, and vanishes on the entire moment-compatible set. Under the standard Wasserstein metric, the energy residual produces a position correction that grows quadratically with the particle speed, and the particle system falls outside standard well-posedness theory. Our primary formulation pairs the quadratic moment mismatch with a velocity-weighted Wasserstein metric that penalizes spatial transport at large peculiar velocity relative to the observed bulk flow, which removes this growth. A direction-split variant retains the plain metric instead. Under the same weighted metric, an alternative moment-relative-entropy functional yields an affine, shape-preserving velocity correction and explicit global moment balances for the space-inhomogeneous system. We prove that the finite-particle scheme with linear Lenard-Bernstein collisions is globally well posed. In 1D1V and 2D2V experiments with several collision models, the nudged formulations reduce bulk-velocity and temperature errors by up to two orders of magnitude relative to an unassimilated run.
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All authors Liyao Lyu, Xinyue Yu, David Schneidinger, Hayden Schaeffer