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Physics Physics Plasma Physics

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Friday 25 September

Plasma Physics

Impact of magnetic drift configuration on the edge radial electric field in the TCV tokamak

S. Rienäcker, L. Vermare, P. Hennequin et al. (+8 more)

The edge radial electric ($E_r$) in the Tokamak à Configuration Variable (TCV) is compared in matched L-mode discharges with opposite ion magnetic drift directions (favorable versus unfavorable $B \! \times \! \nabla B$ configurations). As previously reported on the WEST and AUG tokamaks, the $E_r$ profile—measured by Doppler backscattering (DBS)—exhibits a "well" just inside the separatrix in the favorable drift case, which is absent or less pronounced in the unfavorable counterpart. This observation holds over a broad range of plasma conditions, notably also in Ohmic discharges with nearly identical edge density and temperature profiles. Density fluctuation characteristics inferred from DBS are not drastically different: Under Ohmic heating, edge fluctuation levels tend to be higher in the favorable configuration, while radial correlation lengths are similar. The edge $E_r$ difference appears uncorrelated with carbon toroidal rotation behavior. Reducing density, or increasing auxiliary heating power tends to accentuate the edge $E_r$ disparity. Plasma current has little impact on both favorable and unfavorable $E_r$ profiles—in contrast to results from WEST. Approaching the L-H transition via auxiliary heating, edge $E_r \times B$ shear and pressure grow more readily in the favorable configuration, and DBS fluctuation levels are reduced relative to the unfavorable case. Overall, our results confirm that the edge $E_r$ sensitivity to magnetic drift configuration is a robust, multi-machine phenomenon, with a plausible connection to confinement level and H-mode access.
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All authors S. Rienäcker, L. Vermare, P. Hennequin, C. Honoré, B. Labit, S. Coda, L. Frassinetti, B. Vincent, O. Panico, Y. Wang, K. Singh

Plasma Physics

Bayesian inference of non-Maxwellian distribution functions from collective Thomson scattering spectra

Kentaro Sakai, ByungJun Kang, Akito Nakano et al. (+1 more)

We investigate Bayesian inference of non-Maxwellian electron distribution functions from collective Thomson scattering (CTS) spectra. We represent distribution functions using multiple candidate models of different complexity and perform inference on synthetic spectra generated from known non-Maxwellian distribution functions. Our analysis demonstrates that a sufficiently flexible model can approximate the overall shape of the ground-truth distribution function. The most plausible model is identified based on model evidence, a statistical measure representing the probability to obtain the observed data given the model. When the candidates include the ground-truth model, the model evidence favors the ground-truth model. Without the ground-truth model as a candidate, the model evidence favors the candidate model with the fewest parameters that adequately approximates the data. The posterior probability density function of the most plausible model reveals the characteristic features and associated uncertainties of the underlying distribution function. The origin of the additional spectral peaks is attributed to a combination of modifications to the dispersion relation and reduced Landau damping. This enables the objective and data-driven identification of distribution functions directly from observed CTS spectra.
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All authors Kentaro Sakai, ByungJun Kang, Akito Nakano, Takeo Hoshi

Thursday 24 September

Plasma Physics

Demonstration of H-mode Error Field Identification in a Single Discharge via Island Healing

E.M. Bursch, A. Xie, J.L. Barr et al. (+15 more)

Non-disruptive compass scan error field identification via island healing is demonstrated on KSTAR in a single H-mode discharge. This method can allow for up to a 75% reduction in the operational time necessary for a complete compass scan by reducing the required discharges from four to one. Previous experiments on DIII-D, JET, and MAST-U have demonstrated the technique in Ohmic and L-mode but required multiple discharges and strong real-time n=1 magnetics diagnostics close to the plasma that are unlikely to be viable for future devices. The results presented here were made possible by implementing a new set of triggering algorithms relevant to fusion pilot plant operation into the KSTAR plasma control system, along with KSTAR's strong RMPs and long pulse lengths. This represents a significant step towards the disruption-free error field identification method being demonstrated for deployment on future disruption-averse tokamaks, including ITER and fusion pilot plants. Steps needed to close remaining gaps to viability are addressed.
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All authors E.M. Bursch, A. Xie, J.L. Barr, S.K. Kim, N.C. Logan, S.M. Yang, J.G. Bak, W. Choi, Q. Hu, J.W. Juhn, J. Kim, J. Lee, N. Leuthold, J.K. Park, C. Paz-Soldan, L. Piron, G. Seo, J. Seo

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

Saturation Mechanism of Cosmic Ray Streaming Instabilities with a Shell Distribution

Mohamad Shalaby, Rouven Lemmerz and Christoph Pfrommer

Cosmic rays (CRs) drive galactic winds and regulate galaxy growth while contributing to heating the central cooling plasma in dense galaxy clusters, making the nonlinear saturation of the instabilities that govern their transport a problem of central importance in astrophysics. Using fully kinetic particle-in-cell (PIC) simulations, we find that the streaming instability driven by CRs with a shell momentum distribution saturates through gyro-phase bunching around driven Alfvén waves. Fluid-PIC (FPIC) simulations with both ideal and Landau closures reproduce the PIC saturation amplitude, and the same gyro-phase bunching mechanism, indicating that nonlinear Landau damping (NLLD) does not determine the saturation level at our simulation parameters ($v_{\rm A} = 0.01c$, $n_{\rm CR}/n_i = 0.01$). Notably, the CR ions fully isotropize in the Alfvén-wave frame in all simulations, including the FPIC run with an ideal closure in which NLLD is entirely absent, showing that this isotropization does not require NLLD. We additionally confirm, using the FPIC ideal closure, that this saturation amplitude is unchanged across a tenfold increase in domain size, indicating that the mechanism is local rather than dependent on domain-scale processes. Together, these results indicate that, at least in this regime, NLLD is not the dominant saturation mechanism for the CR streaming instability, in tension with common assumptions built into CR transport models used in galaxy formation and interstellar medium simulations. Whether this conclusion extends to the lower CR densities and Alfvén speeds characteristic of the interstellar medium remains an open question that we address in an upcoming work.
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Plasma Physics · Cross-listed from astro-ph.SR

Non-linear dynamo waves in magnetized shear flows: a candidate mechanism for the solar cycle

Uddipan Banik

Large-scale magnetic reversals in planets, stars, and accretion disks require a non-linear theory coupling the magnetic field to its sustaining flow. We derive exact non-linear solutions to incompressible magnetohydrodynamics in background rotational shear, with large-scale velocity and magnetic fields linear in position (affine form). They reveal a cyclic feedback between meridional circulation, shear, magnetic tension, induction, and the Coriolis force. The steady-circulation reversal orbit, or dynamo wave, periodically reverses all magnetic components and supports slower modulations. In the solar near-surface shear layer (NSSL), moderate shear permits stable 11-year reversals with poleward speeds of 8-12 m/s and poloidal and toroidal amplitudes of 4-11 G and 2.2-3.8 kG near 1 Mm depth, in reasonable agreement with regional observations. At stronger shear, an 88-year reversal exhibits a 203-207-year modulation, reproducing the Gleissberg and Suess-de Vries activity timescales but requiring weaker poloidal fields. Such reversals, however, remain observationally unestablished. At tachocline density, an 11-year reversal and the inferred return flow require toroidal fields of hundreds of kilogauss over a broad shear range, exceeding large-scale-field reconstructions but partly permitted by seismic upper limits. This favors a shallow NSSL origin for a local cycle, while leaving open the issue of a global dynamo. Toroidal dominance prolongs the cycle because shear acting on a weak poloidal field changes only a small fraction of the stronger toroidal field per rotation. Balancing the weak magnetic torque against advection and the Coriolis force also requires slow circulation, which gradually turns the poloidal field and reverses toroidal induction. Efficient poloidal regeneration would shorten this delay. A long solar cycle therefore favors a primarily shear-driven dynamo.
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Plasma Physics

Singularities of the cold plasma theory: Modeling challenges for ICRF operation in low-density edge plasma

Wouter Tierens, Chris Klepper, Raymond Diab et al. (+1 more)

Sustained ICRF operation in a fusion power plant may require low edge densities to mitigate plasma-wall interactions, a regime which was recently achieved in WEST with very little impurity sputtering. Cold plasma theory, however, predicts singular radiofrequency electric fields in this regime, both at the lower hybrid resonance and along the resonance cones, raising the question of whether standard collisional cold plasma models suffice to describe low-density edge ICRF at all. Collisions in principle remove these singularities, replacing them with finite but sharply peaked fields. We derive these peak length scales analytically and confirm them with a 2D finite-element simulation using exponential mesh refinement, achieving micrometer resolution where needed. We conclude that edge collisions in cold plasma do not remove the need to resolve length scales ordinarily associated with hot-plasma and Bernstein-wave physics.
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All authors Wouter Tierens, Chris Klepper, Raymond Diab, Guillaume Urbanczyk

Plasma Physics · Cross-listed from cond-mat.mtrl-sci

From Processing to Functionality: Engineering Accessible Material States in Cu-Embedded SiO$_x$ Memristive Devices

Tobias Gergs, Rouven Lamprecht, Sahitya Yarragolla et al. (+5 more)

Resistive switching in oxide-based devices is widely governed by stochastic defect processes, yet a predictive link between fabrication conditions and functional behavior remains elusive. Here, we establish a multiscale framework connecting plasma-defined deposition conditions to macroscopic device functionality in sputtered SiO$_x$/Cu/SiO$_x$-based systems. By combining large-scale statistical analysis of more than 50,000 experimentally characterized devices with physics-based plasma and atomistic simulations, we show that device behavior does not emerge from deterministic process-to-performance mappings, but from a probabilistic cascade spanning defect formation, defect-state evolution, and functional-regime emergence. Data-driven clustering reveals a continuous functional state space composed of operational switching types, while inverse modeling identifies the reconstructed oxygen-vacancy density as an effective latent descriptor capturing the combined influence of structural disorder and defect topology. This latent descriptor is strongly coupled to both Cu redistribution and electrical response, linking otherwise hidden material properties to observable device characteristics. Furthermore, macroscopic switching behavior is argued to arise from ensemble integration across spatially heterogeneous subdomains, providing a physical explanation for the pronounced variability of large-area devices. These findings shift the perspective from deterministic defect engineering toward probabilistic defect-state design and establish a physically grounded framework for understanding and controlling functional variability in such oxide-based systems, such as memristive or resistive-switching devices.
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All authors Tobias Gergs, Rouven Lamprecht, Sahitya Yarragolla, Ole Gronenberg, Luca Vialetto, Hermann Kohlstedt, Thomas Mussenbrock, Jan Trieschmann

Plasma Physics

Study of low-frequency core-edge coupling in a tokamak: III. Core-localized MHD continuum pulsations & distant forced reconnection

Andreas Bierwage, Panith Adulsiriswad, Gyungjin Choi et al. (+2 more)

Slow magnetoacoustic pulsations (SMAPs) are found in MHD simulations of a tokamak plasma whose safety factor $q$ near the center is flat and slightly above unity ($q \gtrsim 1$). SMAPs are located on the central plateau of the slow magnetoacoustic continuum $\omega_{\rm S} = k_\parallel c_{\rm S}$, where $c_{\rm S}$ is the speed of sound and $k_\parallel$ the wavenumber parallel to the magnetic field. In our model, SMAPs exist when the ion viscosity and thermal diffusivity are sufficiently low. They can be driven unstable by a pressure gradient in the $q \sim 1$ region when the electric resistivity is sufficiently high. Exponentially growing SMAPs consist of standing slow waves on magnetic surfaces that are radially synchronized into a quasi-interchange structure with poloidal/toroidal mode numbers $m/n=1/1$. After free energy depletion, saturated quasi-linear pulsations (alternating $n=1$ and $0$) in the central $q\sim 1$ region couple to distant $q\geq 2$ rational surfaces that undergo "reversible" magnetic reconnection: as the magnetic islands wax and wane with period $2\pi/\omega_{\rm S}$, their X- and O-points alternate. These results show how the MHD model facilitates non-local coupling of slow waves, pressure-driven resistive interchange and tearing. This motivates further study in kinetic models, where collisionless mechanisms for fast reversible reconnection exist and proper treatment of parallel dynamics will allow to assess the role of Landau damping as well as the question whether the ${\mathbf B}$ field's weak ergodicity in the $q\sim 1$ region allows the waves to outpace the ion's parallel streaming to maintain the thermal misbalance underlying SMAPs. Also of interest are pulsations closer to the Alfvénic branch, satisfying $\omega \approx k_\parallel v_{\rm A}$ with Alfvén speed $v_{\rm A}$, which require no resistivity and are less dependent on thermal misbalance.
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All authors Andreas Bierwage, Panith Adulsiriswad, Gyungjin Choi, Young-chul Ghim, Masatoshi Yagi

Plasma Physics

Quasi-symmetric error field correction and applications to ITER

Gwang-Geun Seo, Jong-Kyu Park, S. J. Han et al. (+1 more)

Reliable correction of nonaxisymmetric error fields (EFs) is essential to the safety and performance of tokamak operation. Although resonant error field correction (EFC) is well established, supported by an improved understanding of 3D plasma response, the residual fields left after resonant EFC remain an open question: they are expected to be predominantly nonresonant, yet can still degrade both confinement and stability. Here we introduce a systematic EFC scheme that minimizes resonant and nonresonant EF effects simultaneously, based on neoclassical torque response computed from self-consistent perturbed equilibria. The scheme extends the method developed for designing quasi-symmetric magnetic perturbations to the case where actual error fields are present. Application to standard ITER target plasmas with a range of intrinsic EF scenarios demonstrates the advantages of this quasi-symmetric (QS) EFC scheme for controlling residual EFs. QS EFC consistently yields low-torque solutions while strongly suppressing resonant response, outperforming single-mode resonant overlap EFC in most cases and approaching the performance of multimodal resonant EFC. We also show that the QS EFC solution varies only tolerably between half- and full-$I_p$ ITER scenarios, despite the greater sensitivity expected from its higher-order nature.
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All authors Gwang-Geun Seo, Jong-Kyu Park, S. J. Han, M. Dubrov

Plasma Physics

Equation of state and transport coefficients of warm dense aluminum from mixed deterministic-stochastic density functional theory

Zi Li, Weijie Li, Cong Wang et al. (+2 more)

Aluminum is a reference standard in high-energy-density research and serves as a liner material in megampere Z-pinch facilities. Using mixed deterministic-stochastic finite-temperature density functional theory, we compute the equation of state and transport coefficients of liquid aluminum up to temperatures of 1000 eV and compare the results with model-based approaches. We find that for T<200 eV the density-functional results differ from the models by more than 10% at high density, with a maximum deviation of over 30% (at T = 10 eV), leading to significant discrepancies in the Hugoniot curve at high compression; the calculated electrical and thermal conductivities deviate from model predictions by 26% to 63% at T~100 eV. We further employ the Drude model and the Epperlein-Haines framework to examine the magnetic-field dependence of the conductivities. These results can provide valuable input data for radiation-hydrodynamics codes.
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All authors Zi Li, Weijie Li, Cong Wang, Ping Zhang, Xianjue Peng

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

Production of a Titanium Ion Beam Using Fluorides and Fluorine-Forming Precursors in an ECR Ion Source

D.K. Pugachev, K.I. Berestov, A.E. Bondarchenko et al. (+7 more)

The production of multiply charged titanium ions is of significant interest for accelerator-based experiments, surface modification technologies, and applications in nuclear physics. Due to the low saturated vapor pressure of titanium at temperatures below 1000 {\deg}C, the generation of titanium ion beams from an electron cyclotron resonance ion source (ECRIS) remains a challenging task. The choice of titanium vapor injection methods into the ECR plasma plays a key role in achieving high ionization efficiency, plasma stability, and reliable long-term source operation. In this work, alternative approaches for the injection of neutral titanium atoms into the ECR plasma are investigated, focusing on the use of fluorine-containing compounds. Titanium fluorides (TiF3, TiF4) possess a relatively high saturated vapor pressure at moderate temperatures, allowing to use standard resistively heated ovens operating up to 1000 {\deg}C. Another method involves the in-situ formation of titanium fluorides inside the plasma chamber via chemical reactions between metal titanium and the dissociation products of sulfur hexafluoride (SF6). These approaches enable controlled and efficient titanium injection into the ECRIS plasma with satisfactory extracted ion beam stability.
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All authors D.K. Pugachev, K.I. Berestov, A.E. Bondarchenko, V.N. Loginov, A.N. Lebedev, E.Yu. Kidanova, K.I. Kuzmenkov, V.E. Mironov, D.S. Podoinikov, D.S. Yakovlev

Plasma Physics

Frequency-inference method for reduced modeling of energetic particle modes (EPM) utilizing resonant auto-optimization remnants of imperfect time-scale separation

Andreas Bierwage, Vinícius N. Duarte, Pablo Oyola et al. (+2 more)

Integrated codes simulating interactions between Alfvén waves and fast ions in tokamak plasmas use perturbative models for the relatively slow processes of instability growth, saturation, chirping and bursting, and transport. Faster processes by which an Alfvén mode's spatiotemporal structure forms are assumed to have been completed within the mode's oscillation period, $\tau_0 \equiv 2\pi/\omega_0$. This separation of time scales underlies the computational efficiency of perturbative models, where the Alfvén mode's time-dependence is reduced to that of a scalar signal $s(t) = A(t)\sin(-\omega_0 t - \phi(t))$ with variable amplitude $A(t)$ and phase $\phi(t)$. For this, accurate input data in the form of a mode's spatial structure $\delta\Phi({\mathbf x})$, damping rate $\gamma_{\rm d}$, and initial frequency $\omega_0$ are required. For modes residing in dense or continuous spectra, $\delta\Phi$ and $\gamma_{\rm d}$ could be estimated from the form of the continua and fast ion orbits, but it is difficult to guess the seed frequency $\omega_0$. Here, we report results of numerical experiments showing that it is possible to find $\omega_0$ using a prompt frequency shift that occurs during the first few $100$ time steps of a simulation. Restarts with the shifted frequency iteratively converge to a value of $\omega_0$ that seems to maximize the resonant drive, suggesting an auto-optimization process. The need for iteration is attributed to the fact that the terms required for rapid frequency adjustments were truncated when deriving the perturbative model. Meanwhile, the fact that partial auto-optimization is possible at all is attributed to the fact that series truncation alone (without filter) does not strictly enforce slowness. Remnants of and cross-talk with faster dynamics still occur in numerical implementations. This entails potential for both uncertainty and utility.
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All authors Andreas Bierwage, Vinícius N. Duarte, Pablo Oyola, Kouji Shinohara, Roscoe B. White

Plasma Physics

PQLS: A Quasilinear Gyrokinetic Transport Solver with a Bayesian Saturation-Rule Closure

F. Wilms, A. Agrawal, J. J. Freigang et al. (+3 more)

Quasilinear models make gyrokinetic turbulent-transport predictions sufficiently fast for integrated modelling, but their predictive capability is limited by two factors: the physical and geometrical applicability of the linear solver, and the validity of the saturation rule used to close the model. We present the Predictive Quasilinear Solver (PQLS), a quasi- linear gyrokinetic transport solver formulated in general magnetic geometry. Its implementation as an eigenvalue solver retains electromagnetic and collisional effects, provides access to dominant and subdominant modes and is differen- tiable with respect to all plasma parameters. Linear benchmarks against GENE reproduce the growth rates, frequencies, and eigenfunctions. We additionally formulate the saturation-rule closure as a Bayesian inference problem that distin- guishes uncertainty in its fitted coefficients from the residual model-form uncertainty. The approach is demonstrated by calibrating the SAT3 rule on PQLS quasilinear weights against published nonlinear CGYRO cases. In addition to improving the robustness of the calibration, the new method also quantifies the uncertainty in each of the fit coefficients. Such uncertainty is propagated through transport calculations to produce error-aware profiles that are compared to the ones obtained from the full gyrokinetic simulation, showing excellent agreement.
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All authors F. Wilms, A. Agrawal, J. J. Freigang, T. F. Neiser, B. J. Frei, O. Meneghini

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

Monte Carlo sampling of first-order QED processes in laser and pulsar plasmas

Verneri Sarjomaa and Joonas Nättilä

Monte Carlo sampling of strong-field quantum electrodynamics processes underpins simulations of high-intensity laser experiments and of astrophysical compact-object magnetospheres. Sampling an event requires the total rate of the process together with the cumulative probability that determines how energy is partitioned between the produced particles. Simulations typically tabulate both in advance and invert the tabulated probability numerically. Here we replace this procedure with elementary-function approximations for synchrotron radiation and the nonlinear Breit–Wheeler process. For each process, we approximate the auxiliary function that sets the total rate, as well as the cumulative probability, with Padé approximants chosen so that the inversion reduces to a quartic equation. This yields the sampled quantum parameter—electron $\chi_e$ or photon $\chi_\gamma$—in closed form. The approximations and the particle spectra sampled from them agree with the exact results to within $1\%$. The procedure requires no lookup tables, no interpolation, and no numerical root finding, and can be inserted directly into radiative particle-in-cell codes.
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Plasma Physics

Prediction of Re-Ignition Times in Dielectric Barrier Discharges

Cristian Flores, Hans Höft, Tomáš Hoder et al. (+3 more)

Discharge ignition events in dielectric barrier discharges (DBDs) self-organise into spatio-temporal patterns with varying degrees of order. The complex dynamics of a DBD and intricate structure of occurring patterns complicate the formulation of predictive, mechanistic descriptions. We present the formulation of a reduced-order model that describes the re-ignition dynamics between consecutive discharges appearing at the same position inside a DBD arrangement. The model is derived from an equivalent electric circuit and validated against fluid-Poisson simulations and experiments performed with a multi-filament arrangement in air-like gas mixtures at atmospheric pressure driven by sinusoidal high-voltage waveforms. The experimental scenarios include a highly ordered regime where discharges ignite at regular time and space intervals generating a pattern stable over several periods, and an unstable regime with discharges appearing at seemingly random positions and times. The model accuracy is assessed in both regimes and it is found that the associated prediction uncertainty provides a quantitative measure of the spatial order of the discharge pattern.
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All authors Cristian Flores, Hans Höft, Tomáš Hoder, Franz X. Bronold, Klaus-Dieter Weltmann, Markus M. Becker

Plasma Physics

The quadratic density response function for non-interacting fermions at arbitrary temperature

Pontus Svensson, Jan Vorberger, Zhandos A. Moldabekov et al. (+5 more)

We develop and implement the quadratic density response function of non-interacting fermions at arbitrary temperature, frequencies, and wave vectors. Starting from a Green's function formulation, we derive the quadratic response and demonstrate its equivalence to the result obtained from the Wigner equation. We further derive the classical limit through a perturbative expansion of the Vlasov equation and demonstrate that the quantum and classical formulations agree in the high-temperature limit. We analyse the limiting behaviour with respect to wavenumber and derive the zeroth harmonic response. Two independent implementations are provided and extensively benchmarked against density-functional theory, canonical path integral Monte Carlo (PIMC), and grand canonical PIMC simulations. As the density response of the interacting electron gas is commonly modelled through the ideal response functions and approximate models for the local field correction, the presented formulation will also allow for more complete explorations of interacting systems. Especially, our efficient implementation, which evaluates the ideal static and dynamic quadratic response functions in less than 0.5 ms on a 1.3 GHz processor, will enable evaluation of quadratic corrections to integrated quantities such as interaction potentials and stopping powers in warm dense matter.
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All authors Pontus Svensson, Jan Vorberger, Zhandos A. Moldabekov, Panagiotis Tolias, Paul Hamann, Xuecheng Shao, Cheng Ma, Tobias Dornheim

Wednesday 23 September

Plasma Physics

Nuclear Fusion Knowledge Graph Guided Edge-Localized Mode Recognition on EAST

Wanli Lyu, Laiqi Qian, Xiao Wang et al. (+5 more)

Edge-localized modes (ELMs) are transient magnetohydrodynamic instabilities commonly observed in tokamak plasmas. Although deep time-series models can learn complex dynamic patterns from multi-diagnostic signals, their predictions are mainly data-driven and lack explicit utilization of ELM physics, plasma operating states, and historical discharge experience. As a result, they may confuse categories with similar temporal patterns, particularly under severe class imbalance. To address this issue, we propose KGF-ELM, a Knowledge Graph Fusion Network for ELM Recognition, and introduce a Knowledge Graph Collaborative Fusion Module (KGCFM) that organizes physical evidence from the current time window, ELM prototypes, relational knowledge graph representations, and similar historical discharge cases into complementary multi-source knowledge representations. KGCFM collaboratively models these knowledge sources through physics prototype matching, graph-structured knowledge encoding, historical case retrieval, cross-evidence consistency analysis, and reliability estimation, thereby generating knowledge representations for enhancing temporal features and correcting classification results. Based on this module, KGF-ELM employs a dual-level reliability-aware fusion mechanism. At the feature level, physical residuals and graph-guided knowledge representations are adaptively incorporated into temporal features according to their reliability. At the decision level, reliability gating, minority-class protection, and bounded knowledge correction are used to safely refine the classification results and reduce the negative influence of unreliable knowledge on the base model.
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All authors Wanli Lyu, Laiqi Qian, Xiao Wang, Qingquan Yang, Zehua Chen, Dengdi Sun, Guosheng Xu, Jin Tang

Plasma Physics

Fusing Global Diagnostic Signals and Spectral Data for Electron and Ion Temperature Profile Prediction on EAST via Attention-based Neural Networks

Xiao Wang, Jiangtao Yu, Zichao Lin et al. (+6 more)

Ion temperature Ti and electron temperature Te are fundamental kinetic parameters for evaluating tokamak plasma confinement, turbulent transport and magnetohydrodynamic stability. Reliable prediction of their spatiotemporal profiles is essential for long-pulse steady-state operation on the Experimental Advanced Superconducting Tokamak (EAST). However, existing EAST diagnostic systems have obvious measurement limitations, including narrow applicable conditions of charge exchange recombination spectroscopy and severe signal degradation of edge temperature diagnostics during long discharges. Classical physics-based transport codes suffer from high computational cost and error accumulation, while existing data-driven models only separately predict Ti or Te relying on spectral data, lacking joint Ti/Te modeling and failing under missing spectral measurements. In this work, we propose a multi-modal (i.e., global macroscopic diagnostic signals and spectral data) fusion attention neural network for simultaneous reconstruction of Ti/Te profiles on EAST. It leverages an adaptive attention module to weight global diagnostic features and suppress noise interference, employs convolutional layers to extract deep spectral representations, and utilizes multi-head self-attention to facilitate cross-modal feature interaction. Two separate prediction heads are constructed to output full radial distributions of Ti and Te. This work builds the first EAST-oriented joint Ti/Te prediction model compatible with operating scenarios without spectral diagnostics. Hierarchical attention mechanisms excavate nonlinear multi-modal correlations to realize high-performance dual-temperature profile prediction. The source code of this paper is available on https://github.com/Event-AHU/OpenFusion/tree/main/TiTe_Prediction
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All authors Xiao Wang, Jiangtao Yu, Zichao Lin, Weidong Chen, Dengdi Sun, Wanli Lyu, Hongming Zhang, Jin Tang, Bo Lyu

Plasma Physics

Simulation of ultracold plasma expansion in homogeneous magnetic field

E. V. Vikhrov, B. B. Zelener and B. V. Zelener

We present molecular dynamics simulation results for an ultracold $^{40}$Ca plasma in a constant, homogeneous magnetic field. The magnetic field induces a significant spatial separation of charges. Furthermore, a significant fraction of the electrons escapes from the region bounded by the ions, in contrast to the case of plasma expansion into a vacuum. This leads to the formation of a quasineutral plasma core containing the remaining electrons and surrounded by an outer, thick ion shell, where the ion density drops sharply. Anisotropy in the ion kinetic energy is also observed, depending on the direction of ion motion relative to the magnetic field lines. The simulation results are in agreement with experimental data on ion dynamics.
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Plasma Physics · Cross-listed from physics.acc-ph

Imaging with GeV muons produced via laser-wakefield-accelerated electrons

M. Dobre, P. Ghenuche, A. Balaceanu et al. (+15 more)

Artificially generated muon beams, with tunable parameters, are highly valuable in imaging objects that are opaque to any other scanning technique. Lower-energy muon beams are currently produced at accelerator facilities, while higher energies have only recently been observed as a result of the interaction of laser-wakefield-accelerated electrons and solid targets. This work focuses on using muography imaging detectors to measure the profile of a muon beam generated via the Bethe-Heitler process and to perform muon imaging in an experimental setup extending up to 42 meters from the muon source. By comparing the data with Monte Carlo simulations, we confirm that the measured beam profile and object imaging are consistent with artificially produced muons of energy of a few GeV. To our knowledge, this represents the first demonstration of imaging dominated by an artificial, laser-driven muon beam.
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All authors M. Dobre, P. Ghenuche, A. Balaceanu, D. Catana, M.O. Cernaianu, D. Dorobantu, R. Lica, V. Malka, D. Martello, I. Mitu, M. Niculescu-Oglinzanu, L. Stan, D. Stanca, P. Tomassini, C.A. Ur, C. Vancea, A. Saftoiu, D. Doria

Plasma Physics

AI-Accelerated Gyrokinetic Predictions of Turbulent Transport for Stellarator Design Optimization and Experimental Planning

R. Michael Churchill, Matt Landreman, Jong Youl Choi et al. (+10 more)

Previous work built AI-based surrogates for a nonlinear gyrokinetic simulation code with the goal of using them for fast, direct calculations of turbulent ion heat flux in stellarator design optimizations and scenario planning for experiments. These AI surrogates were trained on data from >200k nonlinear, adiabatic electron gyrokinetic simulations with the gyrokinetic flux-tube code GX, using a wide range of stellarator magnetic configurations ($\sim$23k), positions in the plasma, and gradient scale lengths. In this paper, we demonstrate the use of the AI-based turbulence surrogate in the optimization of stellarator magnetic equilibrium and to speed up stellarator transport solvers. Due to its speed ($\sim$ms), the AI-based surrogate enables previously unattainable optimization objectives, such as full radial profiles of ion turbulent heat flux, or directly optimizing to maximize the turbulent critical gradient at multiple locations across the plasma. These direct calculations provide a potentially more accurate optimization target and reduce reliance on ad-hoc heuristics that may not accurately capture the variation of turbulent transport with magnetic configuration. By including the AI-based surrogate for turbulent heat flux in a transport solver, we can quickly postprocess and confirm the improved ion temperature resulting from the optimized equilibrium. Finally, we demonstrate the use of AI agents with strong reasoning AI models to automate the outer loop, exploring many objective and hyperparameter configurations with this AI-based turbulence surrogate to discover improved turbulence optimized magnetic equilibria.
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All authors R. Michael Churchill, Matt Landreman, Jong Youl Choi, Byoungchan Jang, Rory Conlin, Noah Mandell, Anima Anandkumar, Valentin Duruisseaux, Jeffrey Larson, Dario Panici, Yigit Gunsur Elmacioglu, Jai Sachdev, Tony Qian

Plasma Physics · Cross-listed from hep-ph

Plasma instability splits axion-photon conversion lines

Elizabeth A. Tolman

The axion coupling to electromagnetism may leave signatures of uncertain nature in astrophysical spectra; one is thought to be a single line centered at the axion frequency $\omega = \sqrt{\left(m_a c^2/\hbar\right)^2 + c^2 k_a^2}$, with $m_a c^2/\hbar$ the axion Compton frequency and $\hbar k_a$ its momentum. If a parametric plasma instability is excited, this signature is transformed into a set of lines, which may be proportionally spaced and linearly polarized. A Crab pulsar signal at a frequency near recent cosmological predictions for the axion Compton frequency has some qualitative similarity to this signature, though this similarity is not evidence that the signal is caused by axions.
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Plasma Physics · Cross-listed from astro-ph.HE

Performance-portable GPU acceleration of the hybrid particle-in-cell code dHybridR

Bricker Ostler, Miha Cernetic and Damiano Caprioli

Hybrid particle-in-cell simulations are widely used to study kinetic processes in collisionless astrophysical and space plasmas, yet the high computational cost of large-scale three-dimensional runs has largely confined production studies to two dimensions or restricted domains. To address this challenge, we present a performance-portable GPU implementation of the hybrid particle-in-cell code dHybridR. The implementation combines OpenMP target offloading with specialized SYCL kernels for the most computationally expensive operations, while preserving a unified CPU-GPU codebase that supports Intel, AMD, and NVIDIA GPUs. On the exascale supercomputers Aurora and Frontier, dHybridR achieves weak scaling efficiencies of $86\%$ to $97\%$ across 49,152 accelerators, and at 256 particles per cell, its full-node GPU throughput is up to $32\times$ that of the vectorized CPU implementation at approximately $90\%$ less energy per particle-update. To our knowledge, no other hybrid particle-in-cell code has reported GPU performance at this scale, leaving dHybridR uniquely positioned to exploit exascale systems. These advances substantially lower the computational barrier to large-scale three-dimensional hybrid-kinetic simulations of collisionless plasmas.
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Plasma Physics

Retrospective on the Design and Implementation of the Milestone-Based Fusion Development Program of the U.S. Department of Energy

Scott C. Hsu, Samuel E. Wurzel and Narayan S. Subramanian

This paper provides a detailed account of the origins, objectives, design, and implementation of the Milestone-Based Fusion Development Program, a public-private-partnership (PPP) program launched by the U.S. Department of Energy's Office of Science in September 2022. The purpose of this program is multi-faceted, with policy, scientific and technological (S&T), and commercialization objectives. Tactically, the program supports privately funded fusion companies in closing S&T gaps toward delivering preliminary engineering designs of their demonstration fusion plants (aka "fusion pilot plants"). The program is a key element of a shift in U.S. fusion strategy, initiated in 2022, to accelerate fusion commercialization by leveraging PPPs. The design of the Milestone Program was underpinned by its authorizing legislation and the U.S. National Academies report Bringing Fusion to the U.S. Grid (2021), and drew inspiration from other PPP programs discussed in this paper. Finally, the paper provides the authors' perspectives and reflections on the strengths/weaknesses of the program as implemented, implementation barriers, and lessons learned, with the intent to inform future PPP programs in fusion and other energy/technology disciplines.
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Plasma Physics

Linear Growth Rate of Compressible Tearing Instability in a Force-Free Current Sheet

Chen Shi and Marco Velli

We investigate the linear growth rate of tearing instability in a resistive force-free current sheet using the linearized fully-compressible magnetohydrodynamics (MHD) equations. Our results show that, as the plasma beta ($\beta$), which is proportional to the ratio of thermal pressure to magnetic pressure, increases, the dispersion relation approaches that of the incompressible tearing mode. As $\beta$ decreases, the growth rate increases but this increase remains finite even in the limit $\beta \rightarrow 0$. The relative increase in the growth rate from $\beta = +\infty$ to $\beta=0$ depends on the Lundquist number, with lower Lundquist numbers showing a more pronounced increase. These findings indicate that, while compressibility has a negligible effect on the growth rate of tearing instability in high Lundquist number regimes, its effect becomes significant at low Lundquist numbers. This suggests that compressibility may influence the critical Lundquist number for the transition from laminar to plasmoid-dominated magnetic reconnection. Moreover, in low-$\beta$ regimes ($\beta < 1$), the generated density perturbation can be substantial, comparable to or even larger than the magnetic field perturbation, even though the growth rate is only slightly modified by the compressibility.
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Plasma Physics

Alfvénic high-frequency oscillations at the pedestal of JET plasmas

Leonor Roque, Paulo Rodrigues, Emilia R. Solano et al. (+2 more)

Long-lived ($\sim 10$ s) high-frequency oscillations (HFOs, $50-450$ kHz) near the plasma edge have been reported and experimentally described in L-H transition studies at JET and AUG. In this work, we show that these HFOs are a general phenomenon observed in various plasma scenarios and compositions (H$^1$, D, D-He$^3$, D-T) under different heating schemes, including pure Ohmic, ICRH and NBI. We demonstrate that dominant axisymmetric ($n=0$) HFOs are Global Alfvén eigenmodes (GAEs) tied to the shear-Alfvén continuum (SAC) minima arising at the plasma edge due to the sharp decrease of the density and increase of the safety factor. This hypothesis is corroborated by the remarkable agreement found between the measured frequencies of HFOs and the SAC minima computed by the ideal MHD code CSMISH for a comprehensive set of JET pulses. This result, along with the fact that HFOs are observed over long time windows and across a variety of plasma scenarios, makes them convenient MHD constraints for accurate equilibrium reconstruction near the edge. In view of this pragmatic application, we derive a first-order analytic expression for the two lowest coupled branches of the $n=0$ SAC, disclosing their dependence (and, consequently, that of the HFOs) on the plasma density, safety factor, and elongation profiles. In addition, we discuss the nature of $n\neq 0$ HFOs observed along with the dominant $n=0$ HFOs.
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All authors Leonor Roque, Paulo Rodrigues, Emilia R. Solano, JET contributors, The Eurofusion Tokamak Exploitation Team

Plasma Physics · Cross-listed from cs.LG

Probabilistic and Geometry Aware Neural Surrogate of Scrape Off Layer Plasma Simulations

Gabriele Gianuzzo, Stefan Dasbach, Fleur Hendriks et al. (+2 more)

Fast surrogates for tokamak boundary-plasma simulation are typically deterministic regressors mapping a global operating point to a flattened vector of cell values. Near the divertor detachment transition the steady state is not reliably single-valued. A point estimate must average over qualitatively different plasma states, and it arrives with no statement of confidence. Moreover, the flattened vector representation discards the geometric structure of the SOLPS-ITER mesh. This work addresses both problems. We unroll the curvilinear mesh into three fixed-size image tensors whose layout preserves cell adjacency and inverts exactly, letting a convolutional network act on the geometry without loss of information. A conditional flow matching model, well suited to highly sensitive systems, is then trained on this representation. The result is an efficient, scalable surrogate that captures multiple plausible outcomes even at sensitive operating points. Along a gas-puff scan, the predictive distribution splits into a hot and a cold mode across an early regime transition. A further check on synthetic data with an injected bifurcation of known size confirms the model recovers both branches rather than their average.
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All authors Gabriele Gianuzzo, Stefan Dasbach, Fleur Hendriks, Sven Wiesen, Vlado Menkovski

Plasma Physics

Anisotropy and energy distribution of leptons and photons in radiative relativistic Alfvénic turbulence

Peng Liu, Xiaochun Wei and Zheng Gong

The anisotropic evolution of relativistic particles in magnetically dominated Alfvénic turbulence is a fundamental process governing nonthermal emissions in high-energy astrophysical environments. In this work, we develop a theoretical framework by deriving scaling equations that characterize the pitch-angle dynamics of leptons and photons across both weak- and strong-radiative cooling regimes. Our model reveals a universal coupling between particle energy and angular distribution, arising from the interplay of field-aligned accelerations, perpendicular drift motions, and radiation reactions. The model can uniquely identify “turning-point energies" that exhibit a nonlinear dependence on the local magnetic field and the energy-injection scale. The validity of this scaling model is confirmed through radiative particle-in-cell simulations. We show that the electron pitch-angle distribution fundamentally dictates photon emission characteristics, further revealing a pronounced statistical correlation between high-energy photon emission and turbulent vortices in the reconnection regions. By bridging the gap between small-scale kinetic interactions and broad-band spectral characteristics, this work provides a quantitative basis for interpreting the hardening of radiation spectra and complex polarization signatures in sources such as pulsar wind nebulae and gamma-ray bursts.
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Plasma Physics

A fully implicit electromagnetic energy- and charge-conserving PIC model for simulations of high-$\beta$ plasma

V.A. Kurshakov and I.V. Timofeev

The paper presents a 3D numerical model of plasma in which a fully implicit PIC method with exact conservation of global energy and local charge is generalized to the electromagnetic case. This opens the possibility of simulating plasma equilibria with a high (up to an extreme) ratio of plasma pressure to magnetic field pressure, which are formed in open magnetic traps. The main goal of this work is to find out whether a fully implicit model, which usually performs numerous nonlinear iterations when solving the coupled Vlasov–Maxwell system, can compete in performance with semi-implicit models that achieve the same conservative properties at the cost of only a single particle push per time step. It turns out that in 3D geometry such competition is quite possible due to the growing computational cost of evaluating the mass matrices in the semi-implicit approach. The software implementation of the proposed numerical model is written in C++ within the parallel xpic code. Testing the code on problems of the development of the Weibel instability and the formation of plasma with extreme pressure showed good agreement between the semi-implicit and fully implicit approaches and made it possible to establish their relative speed.
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Plasma Physics

Calibration of cross-field transport models in SOLPS-ITER on the TCV-X21 case

Stefano Carli, Reinart Coosemans, Claudia Colandrea et al. (+1 more)

Cross-field turbulent transport remains one of the largest uncertainties in edge plasma simulations and is commonly approximated through empirical transport coefficients. In this work, we calibrate and assess several cross-field transport models implemented in SOLPS-ITER using measurements from the TCV-X21 reference case. The considered models range from conventional constant-diffusivity descriptions to the self-consistent k-model, in which anomalous diffusivities evolve along with plasma conditions. Model parameters are estimated through gradient-based optimization by minimizing discrepancies between simulated and experimental upstream and divertor profiles in forward field configuration. The calibration results show that increasing the number of free parameters substantially improves agreement with the calibration dataset. However, these more flexible models exhibit poor predictive capability when applied to the reversed field configuration, indicating overfitting. In contrast, the simplest constant-diffusivity model provides the best overall predictive performance while requiring only a small number of calibrated parameters. The k-model achieves a calibration quality comparable to the constant-diffusivity model and reproduces the experimental profiles with similar accuracy, while simultaneously providing a physics-based description of the spatial variation of anomalous transport. Predictions for a density scan reveal differences that are not apparent near the calibration point. The k-model predicts increasing transport levels around the separatrix with increasing density, leading to broader upstream profiles and an earlier onset of divertor rollover compared to the constant-diffusivity model. The presented framework provides a systematic and efficient route for model calibration in SOLPS-ITER, and a set of calibrated k-model parameters to be employed in future studies.
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All authors Stefano Carli, Reinart Coosemans, Claudia Colandrea, Wouter Dekeyser