Helicon
GPU-Accelerated Magnetic Nozzle Simulation & Detachment Analysis Toolkit for Fusion Propulsion
Helicon wraps and extends WarpX with:
- Curated input configurations for magnetic nozzle geometries (solenoid, converging-diverging, FRC exhaust)
- Post-processing pipelines that extract thrust, Isp, detachment efficiency, and plume divergence from PIC output
- Parameter scan and optimization infrastructure (Bayesian, gradient-based via MLX, Sobol sensitivity)
- Validation cases against published analytical solutions and experimental data (VASIMR VX-200, Merino-Ahedo)
- Native Apple Silicon GPU execution via warpx-metal (SYCL → AdaptiveCpp → Metal)
- Detachment analysis suite: MHD onset, kinetic FLR corrections, sheath coupling, Lyapunov controller
Quick Install
pip install helicon
# For Apple Silicon GPU acceleration:
pip install helicon[mlx]
# For Bayesian optimization:
pip install helicon[optimize]
Quick Start
Metal GPU simulation (Apple Silicon)
helicon run --preset sunbird
# WarpX Metal: 42%|████▏ | 210/500 [03:22<04:39, 1.04step/s]
# Simulation complete (287.4s)
Detachment analysis
Environment check
from helicon.fields.biot_savart import Coil, Grid, compute_bfield
from helicon.optimize.analytical import screen_geometry
coils = [Coil(z=0.0, r=0.12, I=50000.0)]
result = screen_geometry(coils, z_min=-0.3, z_max=2.0)
print(f"Mirror ratio R_B = {result.mirror_ratio:.2f}")
print(f"Thrust efficiency η_T = {result.thrust_efficiency:.3f}")
print(f"Plume half-angle θ = {result.divergence_half_angle_deg:.1f}°")
Why Helicon?
The unsolved problem: Plasma detachment in magnetic nozzles is where fusion thrust is won or lost. Current detachment efficiency estimates span 50–95% — a factor-of-two uncertainty that determines whether direct-fusion-drive missions to Mars are 90 days or 9 months.
What makes Helicon different:
| Tool | Gap |
|---|---|
| WarpX | No propulsion-specific postprocessing |
| MN1D (Ahedo group) | 1D only, not public |
| BALOO (Merino) | Not publicly available |
| PlasmaPy | No PIC integration |
Helicon is open-source, GPU-accelerated (MLX on Apple Silicon, CUDA via WarpX), and validation-first.
Citing Helicon
See CITATION.cff or cite as: