The Flux-Coordinate Independent (FCI) approach in the edge fluid turbulence code GRILLIX has proven very successful for tokamaks in handling anisotropic turbulent structures in complex diverted geometries. We extend GRILLIX to non-axisymmetric geometries, maintaining a single, unified codebase for both tokamaks and stellarators. For this proof of principle, the 3D magnetic configurations are based on analytical expressions, that can be adjusted to experimental scenarios, and we demonstrate the code's ability to resolve stellarator geometries correctly via various numerical tests and verifications. We apply the global electromagnetic drift-reduced Braginskii fluid model with trans-collisional extensions and a three-moment fluid neutrals model to two distinct cases. In the first case, we simulate a configuration with imposed magnetic islands and observe profile flattening across the island on time scales consistent with analytic theory. In the second case, we perform a comprehensive turbulence simulation of the Wendelstein 7-AS (W7-AS) stellarator at realistic parameters, including segmented target plates modeled via the immersed boundary approach. Following an initial transient phase, the plasma settles into a self-consistent equilibrium state with Shafranov shift. We then observe smallscale turbulence, characterized by strong elongation along magnetic field lines, which drives turbulent cross-field transport of particles and heat, ultimately directed to target plates in the open field line region. Notably, a parallel mode reflecting the discrete toroidal symmetry of W7-AS is also present. Furthermore, we introduce a novel approach for visualizing data from locally aligned numerical frameworks.

A central unresolved question in fusion energy research is whether energetic alpha particles, the primary products of deuterium-tritium fusion reactions, enhance or degrade plasma confinement. In burning plasmas, the operating regime of future devices such as ITER and SPARC, alpha particles become the dominant heating source, yet their impact on confinement has remained uncertain. Here, we present self-consistent simulations of burning plasmas that simultaneously evolve microturbulence, alpha-particle heating, and macroscopic plasma profiles to steady state, and find that alpha particles can substantially improve confinement. Fusion-born alpha particles weakly destabilize toroidal Alfven eigenmodes (TAEs), which nonlinearly enhance zonal flows that shear apart and suppress ion-scale turbulence. The resulting reduction in turbulent heat transport drives stronger core profile peaking, increasing alpha heating by up to 25% and establishing a self-reinforcing feedback loop. This mechanism has no direct analogue in present-day experiments, where external heating dominates, and reveals an intrinsic pathway toward improved confinement in burning plasmas.

Plasma turbulence is a fundamental process and a key transport mechanism in magnetic confinement fusion (MCF). Due to its complex, non-linear dynamics, turbulence is typically studied through numerical simulations. While turbulence in the confined core plasma has been extensively researched for decades, recent focus has shifted toward the plasma edge and scrape-off layer (SOL). This region, although more challenging to study, is critically important as it sets the boundary conditions for the core plasma and governs physical fluxes to plasma-facing components. This holds true for both major MCF concepts: tokamaks and stellarators. In this work, we introduce a first-of-its-kind tool capable of investigating non-local gyrokinetic turbulence in the edge and SOL of both tokamaks and stellarators. The gyrokinetic turbulence code GENE-X, initially developed for tokamak simulations, has been extended to accommodate stellarator geometries. Here, we detail the modifications made to the code, describe the verification of its new capabilities, and present its first application: the study of turbulence in a stellarator configuration featuring a non-segmented island divertor. This constitutes the world’s first simulation of Eulerian gyrokinetic turbulence in the edge and SOL of stellarators.

Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchronization overheads, and inefficient utilization of multiple accelerators. In this work, we present a portable, multi-GPU hybrid MPI+OpenMP implementation of BIT1 that enables scalable execution on both Nvidia and AMD accelerators through OpenMP target tasks with explicit dependencies to overlap computation and communication across devices. Portability is achieved through persistent device-resident memory, an optimized contiguous one-dimensional data layout, and a transition from unified to pinned host memory to improve large data-transfer efficiency, together with GPU Direct Memory Access (DMA) and runtime interoperability for direct device-pointer access. Standardized and scalable I/O is provided using openPMD and ADIOS2, supporting high-performance file I/O, in-memory data streaming, and in-situ analysis and visualization. Performance results on pre-exascale and exascale systems, including Frontier (OLCF-5) for up to 16,000 GPUs, demonstrate significant improvements in run time, scalability, and resource utilization for large-scale PIC MC simulations.

We demonstrate a turbulence mechanism that reconciles high plasma confinement with efficient heat exhaust—a central challenge for fusion energy. Global two-fluid turbulence simulations of the reactor-relevant quasicontinuous exhaust regime on the ASDEX Upgrade tokamak reveal that a quasicoherent mode drives mesoscopic oscillations of the pedestal boundary across the magnetic separatrix and ejects ballistic filaments (blobs), reproducing both the mean profiles and turbulent fluctuations observed experimentally. This behavior arises from a synergistic interplay between kinetic ballooning modes and resistive X-point modes straddling the separatrix. These first-principles results place extrapolations to future fusion reactors on a firm physical footing.

Numerical modeling of the edge and scrape-off layer (SOL) must account for atomic processes such as hydrogenic ionization and recombination, charge-exchange, and line radiation. Their reaction rates depend non-linearly on density and temperature and are thus sensitive to turbulent fluctuations, whose inclusion/omission may significantly affect model outcomes. We quantify the impact of fluctuations by studying global turbulence simulations of the edge and SOL of ASDEX Upgrade in both attached and detached divertor conditions. While the effect of fluctuations is minimal for the attached state, pronounced localized discrepancies emerge in colder, detached conditions. The inclusion of turbulent fluctuations, when compared to mean-field calculations, causes a factor of 2 reduction in ionization and radiation rates local to the detachment front in the confined edge region. The effect arises from fluctuations crossing below the ionization energy threshold, facilitated by low mean temperature and increased fluctuation amplitudes at the detachment front. The rate reduction (rather than rate increase) is explained by the character of divertor fluctuations (negative density-temperature correlation, i.e., cold and dense blobs), notably distinct from characteristic fluctuations found at the outboard-midplane (positive correlation, i.e., hot and dense blobs). Furthermore, the cold and dense fluctuations enable efficient plasma recombination even at average temperatures above the recombination threshold. In detached conditions, the combined plasma particle source from ionization and recombination is, therefore, effectively reduced by at least 50% when compared to the standard mean-field source.

Collisionless shocks play a key role in space and astrophysical plasmas, enabling the conversion of large-scale kinetic energy into heat and non-thermal particle populations without relying on binary Coulomb collisions. Instead, these shocks are sustained by collective effects such as wave-particle interactions that are inherently kinetic and often nonlinear. Despite significant observational and theoretical efforts, the precise mechanisms and spatial localization of energy dissipation in collisionless shocks remain debated. While it is widely accepted that dissipation occurs within the shock ramp, simulations and observations have shown that energy conversion may also extend upstream and downstream, involving shock structures such as the foot and overshoot. Observational studies using Magnetospheric Multiscale (MMS) have further highlighted that ion heating are often concentrated in the ramp and foot, while electron heating may remain nearly constant or increase only under specific conditions such as enhanced wave activity in the transition region.We analyze high-resolution measurements from the MMS mission across multiple quasi-perpendicular bow shock crossings. We quantify energy contribution of different particle species within a vicinity of the shock ramp to analyze energy transfer among electrons, ions and electromagnetic fields within collisionless shocks. By correcting the measured ion and electron distribution functions for instrumental effects, we isolate the energy contributions of each species and examine how they vary throughout the shock structure. We calculate the theoretically expected values for thermal energy from mass conservation principles and Rankine-Hugoniot conditions to analyze the observed deviation from adiabatic behavior in collisionless shocks. Finally, we discuss how energy transfer between species depends on various shock parameters.

Accurate modeling of turbulent transport in magnetic confinement fusion devices requires extending first-principles gyrokinetic simulations from the core to the edge and scrape-off layer (SOL), where additional physics-particularly plasma-neutrals interactions-must be included. Neutrals in these regions reshape radial profiles, influencing gradient-driven instabilities, and modifying transport across the separatrix and in the SOL. We present a tightly coupled scheme between a continuum gyrokinetic plasma model and a simplified fluid model for neutrals. Specifically, we extend the full-, electromagnetic, collisional code GENE-X with a neutrals density evolution equation, where charge exchange is treated as a diffusive process. This hybrid approach represents a first step toward a consistent fluid treatment of neutrals within gyrokinetic plasma simulations. We focus here on the derivation and implementation of Krook-type source terms for ionization, recombination, and associated radiative losses. These operators are constructed to ensure strict conservation of mass, total momentum, and total energy, including kinetic, binding, and radiative components. The coupling is verified in terms of its numerical convergence and in three-species relaxation tests (with electrons, deuterium ions, and neutral deuterium), with a particular focus on its impact on plasma moments, as well as, the distribution functions. Results indicate that even with a simplified neutrals model, the coupling introduces kinetic modifications to the plasma, whose influence on macroscopic quantities will need to be assessed in forthcoming turbulence simulations.

Abstract This work presents a stepwise validation of the evolution of the radial electric field E r and transport during the pre L–H transition phase in the ASDEX Upgrade (AUG) tokamak using edge and scrape-off layer full- f gyrokinetic simulations including X-point geometry. Several L-mode time slices up to the L–H transition from a dedicated hydrogen discharge, featuring stepwise increases in electron cyclotron resonance heating input power, are selected (Bonanomi et al 2024 Phys. Plasmas 31 072302) and simulated with the GENE-X code. As the edge boundary conditions are progressively increased between the time slices, particle and heat fluxes rise, and the radial electric field E r well deepens. A detailed validation of the E r profiles and of the E r well depth shows excellent agreement with experimental measurements at the successive time slices approaching the L–H transition. A force balance decomposition identifies turbulence-driven poloidal flows as the dominant contribution within the E r well. Edge turbulence is governed by a competition between electron drift waves and trapped-electron modes. The introduction of an edge density source, modeling neutral gas ionization, is shown to be essential to reproduce experimentally relevant density profiles, E r , and edge ion heat fluxes, which are dominated by both turbulent and diamagnetic contributions. This stepwise validation constitutes an important milestone toward predictive, first-principles gyrokinetic simulations of the L–H transition power threshold.

We demonstrate a mechanism for reconciling high confinement with heat exhaust in fusion plasmas. Global fluid turbulence simulations of the Quasicontinuous Exhaust regime in the ASDEX Upgrade tokamak show that a quasi-coherent mode (QCM) causes the pedestal foot to oscillate across the separatrix and eject ballistic blobs into the scrape-off layer (SOL), reproducing not only mean profiles but also fluctuation spectra and mode structure seen in experiments. The QCM is a kinetic ballooning mode that develops an extended radial correlation length via electromagnetic self-organization of turbulence, thereby driving enhanced transport, with Maxwell stress and finite Larmor radius effects mediating the process. The blobs are launched when resistivity excites a secondary mode that originates from the X-point and interacts with QCM. The blob-dominated SOL temperature fall-off is then well decoupled from the pedestal-foot gradient set by the QCM.

The pedestal region in tokamak plasmas plays a critical role in determining overall confinement and performance, yet the interplay between turbulence and plasma shaping within this region is not fully understood. In this work, we present a comprehensive characterization of pedestal instabilities and their sensitivity to plasma shaping effects using the gyrokinetic code GENE. We consider a well documented H-mode discharge at two different time points where the plasma shaping is varied at constant beta pol. Local linear simulations reveal microinstabilities present at all scales in both shaping cases. Global nonlinear simulations show a turbulence reduction with increased shaping, leading to an increased pedestal density in the high shaping case. At electron scales, the nature and impact on transport of these modes is assessed, confirming a significant amount of heat-flux driven at such scales while comparing with novel reduced models. Finally, the heat transport is compared with experimental fluxes across different transport channels with either correct order of magnitude or better agreement.

A power ramp from L- to H-mode-like conditions is carried out in a 50 ms long global full-f turbulence simulation of ASDEX Upgrade with the grillix code. After 32 ms of slow profile evolution, a sudden change in transport triggers a pedestal buildup within ∼100  μs. This transition results from an abrupt shift from drift-wave (DW) to kinetic-ballooning-mode (KBM) turbulence. The self-consistently evolved E×B flow shear first increases slowly and then sharply. Geodesic acoustic mode and Alfvénic flow oscillations intensify prior to the transition and subsequently die out. This is followed by slow oscillations of the transport and profiles, reminiscent of a dithering I-phase or edge-localized-mode (ELM) cycles observed experimentally. This study paves the way for a better understanding of confinement regime transitions.

We present iGENE, a fully-differentiable TensorFlow implementation of the electromagnetic local nonlinear gyrokinetic model, which allows us to compute gradients of any simulation output with respect to any input via automatic differentiation. We show that even if the stochastic nature of turbulence prevents the exact evaluation of gradients of nonlinear quantities of interest, they can still be successfully used to perform outer-loop tasks, such as profile predictions. This work enables the integration of gyrokinetics into automated parameter optimization, uncertainty quantification, sensitivity analysis, and AI workflows.

Pedestal relaxation events (PREs) appear in I-mode discharges close to the I-H transition. Although they show certain similarities with edge localized modes (ELMs), i.e., periodic energy ejections, the underlying mechanism seems to be very different from the mechanism responsible for ELMs. In this manuscript, we present global trans-collisional fluid simulations of an I-mode discharge in ASDEX Upgrade using GRILLIX. We observe multiple PREs during the simulation, which reproduce a range of experimentally observed PRE characteristics. Furthermore, a detailed analysis of various mode properties in our simulation allows us to pinpoint the underlying mechanism responsible for triggering PREs to micro-tearing modes (MTMs). The system is analyzed dynamically by evaluating density and electron temperature gradient lengths at the OMP position, where the MTM is located and grows over time. The path taken by the system in gradient length space is compared to a growth-rate estimate calculated by linear theory in simplified slab geometry, providing excellent agreement. Building on these insights, we sketch a qualitative picture of a full PRE cycle. Finally, we discuss the influence of the recently implemented Landau-fluid closure and the challenges of simulating low collisionality regimes with trans-collisional fluid models, like the one employed by GRILLIX.

ABSTRACT Turbulence in the edge and scrape‐off layer regions plays a critical role for the performance of future magnetic confinement fusion power plants. Gyrokinetic simulations allow studying this regime with high fidelity. A key aspect in these regions is the high concentration of impurities, which can radiate energy, leading to significant losses. Due to large mass and high charge state, impurities are highly collisional, making them difficult to model accurately. This work presents discretization and algorithmic improvements for Lenard‐Bernstein collisions in gyrokinetic simulations based on previous conservative finite‐volume scheme. The new discretization improves numerical consistency by eliminating conservation errors, which were previously circumvented through the use of free parameters. While small boundary corrections remain necessary, we show that numerical conservation can be improved through careful stencil design, reducing reliance on free parameters. Its implementation is verified through conservation and relaxation tests. The algorithmic improvements focus on computational performance, achieving compute and communication performance gains in a scaled‐down TCV‐X21 benchmark. It also scales as with the number of species , significantly improving upon the previous naive implementation.

Constructing reduced models for turbulent transport is essential for accelerating profile predictions and enabling many-query tasks such as parameter exploration, uncertainty quantification, and design optimization. This work investigates machine-learning-driven reduced models for electron temperature gradient (ETG) turbulence in the Wendelstein 7-X (W7-X) stellarator. We develop physics-guided scaling laws to predict the ETG heat flux at seven radial locations as functions of three key plasma parameters: the normalized ETG ( omega(Te)), the ratio of normalized electron temperature and density gradients ( eta(e)), and the electron-to-ion temperature ratio ( tau). The model coefficients are determined through regression combined with an active learning strategy. The procedure initializes the scaling laws using low-cardinality sparse-grid training data and iteratively enriches the training set by selecting maximally informative samples from an existing simulation database. The predictive performance of the models is assessed using out-of-sample datasets comprising more than 393 points per radial location. Using the coefficients identified at the seven training radial locations, we further derive regression-based parameterizations for the scaling-law coefficients as functions of radial position. The resulting models are then evaluated at three additional radial locations not used during training, including both interpolation and moderate extrapolation cases. Overall, our reduced models demonstrate good predictive performance and achieve accuracy comparable to the original reference simulations, including in interpolation and moderate extrapolation regimes. An important finding is that a single radius-independent model cannot adequately describe ETG transport across the W7-X core, suggesting the presence of geometry-dependent physics not captured by the present formulation.

Efficient simulation of complex plasma dynamics is crucial for advancing fusion energy research. Particle-in-Cell (PIC) Monte Carlo (MC) simulations provide insights into plasma behavior, including turbulence and confinement, which are essential for optimizing fusion reactor performance. Transitioning to exascale simulations introduces significant challenges, with traditional file input/output (I/O) inefficiencies remaining a key bottleneck. This work advances BIT1, an electrostatic PIC MC code, by improving the particle mover with OpenMP task-based parallelism, integrating the openPMD streaming API, and enabling in-memory data streaming with the ADIOS2 Sustainable Staging Transport (SST) engine to enhance I/O performance, computational efficiency, and system storage utilization. We employ profiling tools such as gprof, perf, IPM and Darshan, which provide insights into computation, communication, and I/O operations. We implement time-dependent data checkpointing with the openPMD API enabling seamless data movement and in-situ visualization for real-time analysis without interrupting the simulation. We demonstrate improvements in simulation runtime, data accessibility and real-time insights by comparing traditional file I/O with the ADIOS2 BP4 and SST backends. The proposed hybrid BIT1 openPMD SST enhancement introduces a new paradigm for real-time scientific discovery in plasma simulations, enabling faster insights and more efficient use of exascale computing resources.

Plasma simulations are among the most computationally demanding scientific workloads, combining high-dimensional kinetic evolution, particle-mesh coupling, field solves, and data-intensive communication. As general-purpose processor scaling slows, post-Moore technologies are being explored to address bottlenecks in data movement, memory access, and power consumption. This paper provides a community perspective on the role of these technologies in plasma simulation, assessing three major classes: reconfigurable and data-path accelerators, non-von Neumann architectures, and quantum computing. Each is evaluated, in a co-design approach, against representative plasma workloads spanning particle-in-cell, continuum Vlasov, gyrokinetic, fluid/MHD, hybrid, and warm dense matter methods. We find that no single technology can replace existing HPC platforms. Instead, three tiers of opportunity emerge: FPGA-class and data-path accelerators offer near-term kernel offload and workflow-level data services, non-von Neumann architectures represent medium-term directions for operator-level acceleration, and quantum computing, although the least mature, is potentially the most disruptive for warm dense matter and inertial confinement fusion microphysics. We outline best practices for selective adoption and identify focused demonstrators, benchmarking, and modular software ecosystems as immediate community priorities.

Controlling the plasma in fusion devices is made challenging by the latency required to react to changes in the plasma state in real time as well as by the limited amount and quality of data available to the plasma control system at discharge time. But precisely these limitations make Machine Learning (ML) and particularly Deep Learning (DL) a promising alternative to traditional approaches in some workflows in plasma control. DL models differentiate themselves by the fact that most of their computational expense is paid upfront during training, where pre-existing datasets are used to tune the models' parameters to the intended task. Training can be computationally demanding. In contrast, inferring, or making predictions, on new data using previously trained DL models is computationally trivial. This fact can be exploited to enable using complex DL models in time sensitive and data constrained real-time applications, such as plasma control. DL particularly benefits from the use of hardware accelerators, like Graphics Processing Units (GPUs), but due to the added latency associated with their use, they are still largely absent from real-time applications, limiting the benefits of using DL. In this contribution we present the technical implementation of a pipeline for the standardized and streamlined training and deployment of real-time capable DL models as augmentations to the ASDEX Upgrade (AUG) Discharge Control System (DCS) Treutterer et al. (2014). A particular emphasis will be put on our simple real-time GPU-accelerated inference implementation based on commonly available tools like TensorRT NVIDIA (2019) and CUDA NVIDIA (2014). The models of our first application predict a high-fidelity electron density profile, based on the measurements of the interferometry diagnostic alone. They approximate the highly accurate Integrated Data Analysis (IDA) Fischer et al. (2010) profiles closely and are resilient to corruption in the input data. The complete latency of the inference process from the time of receiving data to the profile being available to the DCS is roughly 30-38 mu s running on an NVIDIA RTX L4 GPU.

A long-wavelength model for the turbulent magnetic fluctuations parallel to the magnetic field ( B1,||) has been implemented in the global gyrokinetic code GENE. The model provides a way to include this physical effect with little computational cost, permitting the study of B1,|| on global nonlinear gyrokinetic simulations. The model has been verified through convergence tests and against an arbitrary wavelength solver, resulting in good performance up to moderately high wavelengths ( ky rho s less than or similar to 1). Using this approximation global nonlinear fully electromagnetic simulations were performed with Cyclone Base Case-like parameters to study the impact of B1,|| on different plasma beta regimes. A negligible impact for a low beta regime and roughly a doubling of the heat transport when including B1,|| in a high beta KBM regime is found, which is in line with expectations based on linear studies and highlights the impact of B1,|| in KBM driven scenarios.