Measurement of spherical tokamak plasma compression in the PCS-16 magnetized target fusion experiment
Bibliographic record
Abstract
Abstract A sequence of magnetized target fusion devices built by General Fusion has compressed magnetically confined deuterium plasmas inside imploding aluminum liners. Here we describe the best-performing compression experiment, PCS-16, which was the fifth of the most recent experiments that compressed a spherical tokamak plasma configuration. In PCS-16, the plasma remained axisymmetric with δ B pol / B pol < 20 % to a high radial compression factor ( C R > 8 ) with significant poloidal flux conservation (77% up to C R = 1.7, and ≈ 30 % up to C R = 8.65 ) and a total compression time of 167 μ s . Magnetic energy of the plasma increased from 0.96 kJ poloidal and 17 kJ toroidal to a peak of 1.14 kJ poloidal and 29.9 kJ toroidal during the compression, while the thermal energy was in the range of 350 ± 25 J. Plasma equilibrium was a low-β state with β tor ≈ 4 % and β pol ≈ 15 % . Ingress of impurities from the lithium-coated aluminum wall was not the dominant effect. Neutron yield from D-D fusion increased significantly during compression. Thermodynamics during the early phase of compression ( C R < 1.7 ) were consistent with increasing Ohmic heating of the electrons due to a geometric increase in the current density at near-constant resistivity, and with increasing ion cooling that approximately matched ion compression heating power. Ion cooling by electrons was significant because the electrons were much cooler than the ions ( T e = 200 eV , T i = 600 eV ). Magnetohydrodynamic simulations were used to model the emergence of instabilities that increase electron thermal transport in the final phase of compression. Conditions for ideal stability were actively maintained during compression through a current ramp applied to the central shaft and, after this current ramp reached its peak two-thirds of the way through compression, we measured a transition in plasma behavior across multiple diagnostics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".