Self-organization of pure electron plasma in a partially toroidal magnetic-electrostatic trap: A 3D particle-in-cell simulation
Bibliographic record
Abstract
The dynamics of a pure electron plasma magnetically confined in a partial toroidal trap is investigated using 3D3V PIC simulation. In particular, a toroid having a rectangular meridian, a tight aspect ratio of 1.6, and a 3π/2 toroidal domain is considered. Externally applied negative end-plug potentials electrostatically seal off the toroidal ends of the device for the confined electron cloud. A homogeneous square-toroidal segment of pure electron plasma is loaded in the middle of the trap. Strong non-uniform sheared poloidal flow reshapes the square cross section into 00an elliptical profile with symmetric closed contours of density peaking in the center. On the toroidal midplane, the plasma gets shaped into a crescent by the opposing dispersing and confining forces of the self-electric field and the end-plug fields, respectively. Density inside the crescent falls symmetrically from the middle to the two tapered ends. The self-reorganization of the loaded square-toroidal segment into an “elliptic-crescent” is completed within a time scale of ∼0.1μs. The cloud then starts to engage in poloidal orbits of the fundamental (toroidal) diocotron mode. The poloidal orbit’s time period is ∼2μs. The first orbit is turbulent and incurs significant electron losses (∼30%) to a particular segment of the poloidal boundary. Subsequent orbits are dynamically stable with a compression–expansion cycle of the cloud as it moves in an out of strong magnetic fields on the poloidal plane. The poloidal compression–expansion cycle is collisionlessly coupled with the toroidal cloud shaping through the self-electric fields and manifests as an elongation–contraction cycle of the crescent on the toroidal midplane. A radical improvement of the device’s confinement is observed when its volume is isotropically compressed keeping other parameters the same. The numerical design of the partial toroidal trap has several novel aspects such as the use of specialized numerical “pseudo-dielectric” layers for producing functional end-plug fields in the numerical device setup.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".