The challenge begins with the nature of gyrokinetic simulations themselves. These simulations are the dominant approach to quantifying turbulent transport in fusion reactors, using codes such as GKW, GENE, CGYRO, and GS2 that have been extensively verified through inter-code benchmarks. Rather than tracking every particle’s full motion, gyrokinetics exploits the fact that in a strongly magnetized plasma, charged particles spiral rapidly around magnetic field lines while drifting slowly. By averaging over this fast gyromotion and representing particles at their gyrocenters, the problem is reduced from an intractable six-dimensional formulation to a five-dimensional one, containing three spatial and two velocity coordinates. This reduction makes the simulations computationally feasible but leaves the raw output, a distribution function in five-dimensional phase space, fundamentally awkward to visualize directly.

Simulation codes typically post-process this distribution function by computing velocity-space moments, yielding field variables such as the electrostatic potential and fluctuations in density and temperature that can be represented in three-dimensional physical space. Even within this reduced three-dimensional setting, producing useful visualizations is non-trivial. The simulation domain is defined in magnetic-field-aligned flux-tube coordinates that follow the field line around the torus, and mapping these coordinates into real physical space requires a substantial geometric transformation. As a result, gyrokinetics specialists have traditionally worked with only a small subset of their output data, such as one-dimensional time traces or fields examined near the outboard mid-plane, limiting the routine use of advanced three-dimensional visualization in the field.

The new workflows, developed by Rui Costa and colleagues at UKAEA’s Computing Division and published in Frontiers in Physics, address this gap by providing a complete pipeline from raw simulation output to final renders. The team designed two related coordinate transformation pipelines to map field-aligned computational data onto real-space Cartesian coordinates. In the spectral-coordinate pipeline, used with the Pyrokinetics framework, perpendicular fields stored as Fourier coefficients are reconstructed in real space via inverse Fourier transforms, then embedded in toroidal geometry using equilibrium-derived flux-surface shapes. A distinctive feature of this path is the explicit enforcement of a parallel closure that provides a phase-consistent periodic extension along the field line, determined by the safety factor and discrete binormal harmonic indices. In the gridded-format pipeline, used with GKW outputs, fields are already sampled on a real-space computational grid and are embedded using an analytically shaped torus model with Miller-like parameters.

Both pipelines share two principal stages: first, the computational domain is embedded in toroidal geometry; second, the resulting cylindrical coordinates are converted to Cartesian coordinates. The pipelines differ in the native coordinates of the input fields, the source of the geometric embedding, whether equilibrium-derived or analytically shaped, and whether an additional closure is imposed along the parallel coordinate. Once transformed, the data are written as Visualization Toolkit (VTK) datasets, one per time step. This intermediate format is the key to the workflow’s flexibility: it decouples data preparation from rendering, allowing the same processed dataset to be reused across multiple visualization environments without repeating the upstream processing.

The workflows support a myriad of gyrokinetic codes including GKW, GyroSwin, GENE, CGYRO, and other workflows based on Pyrokinetics, a Python library designed to standardize gyrokinetic analysis across different simulation tools. Rather than developing separate preprocessing routines for each code, the team uses Pyrokinetics as a common interface wherever it can provide the required field data and geometry information. For GyroSwin, a recently introduced five-dimensional neural surrogate model that reduces the computational cost of fully resolved gyrokinetic simulations by three orders of magnitude, the workflows require an additional repadding step. This is because the electrostatic potential inherited from GKW carries real-FFT padding used in the original code, creating a spatial dimension mismatch with the associated five-dimensional distribution-function data that must be resolved before the surrogate predictions can pass through the same downstream processing as reference simulations.

Once the VTK datasets are generated, the team’s workflow branches into three rendering environments, each suited to different needs and end users. ParaView, a widely used open-source scientific visualization platform, is best suited to day-to-day scientific analysis by expert users and to the production of accurate, high-fidelity visualizations for publications. Its Python scripting interface makes it straightforward to build reproducible rendering pipelines. Blender, though not designed specifically for scientific visualization, offers a physically based Cycles renderer well suited to producing images for broader audiences, with a flexible material system that makes it straightforward to build custom shaders combining emissivity, opacity, and color mapping to encode multiple field variables simultaneously. NVIDIA Omniverse provides real-time interactive visualization within a USD-based environment, useful for local and remote exploration of datasets too large to inspect frame by frame in a traditional post-processing workflow.

The team demonstrated the workflows’ capabilities through multivariate visualizations of potential, density, and temperature fluctuations rendered within tokamak geometry. In one striking example, the turbulent electrostatic potential was rendered as a semi-transparent volume with a custom shader mapping color to the potential value, opacity to the density fluctuation, and emission to the temperature fluctuation, producing a single volume that simultaneously encodes three physically meaningful fields. This multivariate approach creates the possibility of directly examining spatial correlations between these coupled quantities, something not available from separate scalar plots. The workflows also support physically motivated preprocessing, such as separating zonal flows, large-scale axisymmetric structures that regulate transport by shearing and suppressing turbulent eddies, from non-zonal turbulent components through binormal Fourier-space filtering.

For interactive inspection, the team developed a custom viewer based on NVIDIA Omniverse Kit and Kit-CAE, coupled to a web application that receives a WebRTC video stream from the Kit session and sends control messages back to the viewer. The browser does not render the data itself; it provides controls for the live Omniverse session, including scene hierarchy, transfer-function controls, volume-render settings, and camera controls. In a representative browser-based session, the application streamed a 1080p viewport at 60 frames per second with zero packet loss and a mean round-trip time of 27.6 milliseconds over a VPN remote-access path. This makes it possible to inspect large datasets from any device on the network, including a laptop or tablet, without installing Omniverse locally, and to share the experience with collaborators in different locations.

The team also quantified the computational cost of the staged workflow through a performance benchmark on a representative GKW run, measuring wall time, CPU usage, peak resident memory, and artifact sizes across low, mid, and high fidelity settings. The results show that the coordinate transformation combined with the increase in grid resolution required for on-screen visualization is the main computational bottleneck: the visualization-ready VTK dataset can be orders of magnitude larger than the original simulation output. However, the per-time-step structure of the VTK export stage is naturally parallel and can be distributed across many independent HPC jobs. The workflows were developed around the needs of UKAEA and the HPC systems used most frequently at the institution, particularly the Cambridge Service for Data-Driven Discovery (CSD3), the local UKAEA HPC cluster, and the local visualization cluster. The team acknowledges several limitations: the current workflows operate on three-dimensional field data rather than the full five-dimensional gyrokinetic distribution function, they are primarily post-processing rather than fully in-situ visualization systems, and the Omniverse viewer currently supports remote inspection of an individual loaded timestep but not time-series playback. Nevertheless, by writing transformed data to a common VTK representation and demonstrating the pathway across multiple gyrokinetic codes and visualization environments, these workflows provide a practical and extensible foundation for routine visualization of gyrokinetic field data, potentially enabling scientists to see fusion turbulence as never before.

Subject of Research: Advanced visualization workflows for gyrokinetics simulation data

Article Title: Advanced visualization workflows for gyrokinetics simulation data

Article References: Advanced visualization workflows for gyrokinetics simulation data. (n.d.). https://doi.org/10.3389/fphy.2026.1924612

Image Credits: AI Generated

DOI: 10.3389/fphy.2026.1924612

Keywords: gyrokinetics, fusion, visualization, tokamak, plasma turbulence, VTK, ParaView, Blender, NVIDIA Omniverse, UKAEA, Advanced, workflows

The new framework, developed by PPPL physicists Luis Delgado-Aparicio, Masayuki Ono, and Jonathan Menard and published in the journal Physical Review Letters, extends the Lawson criterion by folding in four additional conditions that any real fusion system must satisfy to reach and hold a burning plasma. In mathematical terms, the updated route to ignition passes through a region known as the Cordey saddle, the lowest point on a ridge that separates a plasma still dependent on external heating from one that burns under its own power. By mapping this terrain, the team could compare different strategies for driving a plasma to ignition and quantify exactly how much heating energy each one demands.

Delgado-Aparicio likens the result to finding the most efficient way through a mountain range. Imagine the energy a plasma needs to reach ignition laid out as terrain, with the point of ignition hidden behind the peak of a tall mountain. Many fusion efforts, he explained, plan to climb straight to the summit by raising the plasma’s density first and then adding heat. The new map shows a better way: heat the plasma first, then raise its density once it is already hot. A lot of companies want to climb the mountain head-on and spend enormous energy to get there, he said. Go around the peak instead. You reach the same place in a much smarter way, and you use far less energy.

The quantity at the heart of this comparison is Q, the ratio of fusion power produced to heating power supplied. In a clean, ideal plasma of pure fuel, the Cordey saddle sits where fusion reactions return roughly five times the heating power put in. That number is not arbitrary; it represents the minimum efficiency a plasma must achieve before the feedback loop of fusion heating can take over completely. But real machines are never ideal, and the PPPL team’s central contribution was to quantify how sharply the required Q rises once real-world effects are included. Adding impurities and super high magnetic fields moves the saddle and raises the Q required to cross it, sometimes dramatically.

The strength of the paper lies in its integration. Earlier theoretical work typically treated loss mechanisms one at a time, which made it difficult to judge how they interact or compound. The PPPL team folded four major effects into a single model. The first is helium ash, the spent product of fusion reactions that can accumulate inside the plasma and dilute the fuel. The second covers light and heavy impurities that enter the plasma from the inner walls of the fusion system, sapping energy from the reacting core. The third is synchrotron radiation, the light given off by negatively charged particles as they spiral in the machine’s magnetic field. The fourth is heat conduction out of the plasma, a loss channel that grows as the temperature rises. Each effect alone is manageable; together, they reshape the entire accessibility landscape for ignition.

When you leave these effects out, you say the design will work fine, Ono said. When you put them in, the picture changes, and it becomes quite important. The aim, he said, is to give the field a shared, more realistic model for judging a fusion design before it is built. The old assumption that the Lawson criterion is a single fixed value leaves out effects that can change the answer sharply. Fusion experiments cost a great deal of money, he noted, and you do not want to make mistakes you could have caught beforehand. In an era when well-funded private companies and national laboratories are committing billions of dollars to first-of-a-kind machines, a tool that screens designs on paper before steel is cut could prove as consequential as any hardware advance.

One of the framework’s most striking findings concerns tungsten, the metal that more than a dozen next-generation fusion machines have chosen for their inner walls. Tungsten is prized because it can withstand the extreme heat flux of a plasma that must reach temperatures hotter than the core of the sun, far beyond what any conventional material could tolerate. But the new research shows that even a trace of tungsten, at a concentration of just one part in 10,000 inside the plasma, can roughly double the pressure needed to reach ignition. That calculation, performed in two dimensions, already represents a steep penalty. Extended to three dimensions, the pressure required to reach ignition can climb past the point where the plasma remains stable, meaning the machine could never reach a burning state at all.

Remarkably, the same physics that makes ignition harder also offers a safeguard. Fusion designers have long worried about a thermal runaway instability, in which fusion heat drives more fusion reactions, which in turn drive more heat, in an uncontrolled amplifying cycle. The PPPL team found that the very losses that raise the ignition threshold, including radiation from impurities and synchrotron emission, push back against that cycle. Together, these mechanisms can hold a burning plasma in a steady state on its own. The safety logic differs fundamentally from fission: a fusion system holds only seconds of fuel at a time, so losing control simply means the plasma cools and the burn stops rather than anything worse. In effect, tungsten contamination acts as a built-in thermostat, capping how hot the plasma can become even as it raises the bar for getting there in the first place.

The paper does not stop at diagnosis; it also points toward remedies. Walls coated with liquid lithium, an approach PPPL has studied for years, can block tungsten from entering the plasma while simultaneously improving heat retention, attacking the contamination problem from both sides. Another option is spin-polarized fuel, in which the nuclei of the fuel are aligned before they fuse, raising the intrinsic rate of fusion reactions and thereby lowering the conditions the plasma must meet. Both strategies would shift the ignition terrain back in the operator’s favor, making the Cordey saddle easier to cross with the heating power available on any given machine.

The research remains theoretical, based on calculations rather than measurements, because no experiment today reaches the temperatures where the Cordey pass sits. But the team plans digital experiments, high-fidelity simulations that can test whether the heat-first route behaves as the framework predicts. While more study is needed, we are excited by these results, and they suggest a clear path forward for future research in this area, Menard said. If the simulations confirm the map, the implications for machine design could be profound: tokamaks and stellarators could be sized, shaped, and heated according to a route that minimizes the energy bill for ignition rather than maximizing it. The work was supported by the DOE Office of Science’s Office of Fusion Energy Sciences under contract DE-AC02-09CH11466, including a 2015 Early Career Award, a 2018 Diagnostic Innovation and Development award, and the 2021 and 2025 Long-Pulse Tokamak Research Programs. For a field that has spent seventy years staring at a finish line, the new framework finally offers something more useful: directions.

Subject of Research: Reformulated Lawson criterion identifying efficient routes to fusion ignition in tokamak and stellarator plasmas

Article Title: A novel path to fusion ignition: Heat first, then add fuel

Article References: A novel path to fusion ignition: Heat first, then add fuel. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: fusion energy, ignition, Lawson criterion, burning plasma, tokamak, stellarator, tungsten, Cordey saddle, synchrotron radiation, plasma physics, Princeton Plasma Physics Laboratory, Physical Review Letters