Monte Carlo Neutral Codes
Monte Carlo neutral codes launch and follow statistical sample particles through collision physics to tally plasma sources in realistic geometry.
The Monte Carlo method for neutrals
A Monte Carlo neutral code represents the neutral gas by a large sample of computational particles. Each is born at a surface or gas source with a sampled velocity, flies in a straight line until a randomly sampled collision, and then either ionizes (removed, depositing a plasma source) or charge-exchanges or scatters (continues as a new neutral). Tallying these events over many particles gives smooth estimates of the ionization, momentum, and energy sources.
The strength of the method is that it handles arbitrary geometry, wall shapes, and detailed atomic and molecular reaction chains without the closure approximations a fluid neutral model requires.
Variance reduction
Raw Monte Carlo is noisy where few particles reach, such as deep in a dense plasma. Codes apply variance-reduction techniques, splitting, Russian roulette, and importance weighting, to concentrate computational effort where the answer matters, keeping statistical error tolerable at reasonable cost.
Atomic and molecular data
Results are only as good as the cross-section and rate-coefficient databases for ionization, recombination, charge exchange, and molecular dissociation. Curated atomic data underpins these codes, and uncertainty in the data propagates into the plasma-source predictions.
Design relevance
Coupled to edge fluid codes, Monte Carlo neutrals are the standard for divertor and recycling simulation. For the Hyperion breeder they quantify fueling penetration and the neutral pressure at the divertor in the design phase, with the statistical and atomic-data uncertainties carried explicitly.
- Sample particles followed through collisions
- Handles complex geometry and reaction chains
- Variance reduction controls noise
- Depends on atomic and molecular databases