On the use of ultra-high resolution PIC methods to unveil microscale effects of plasma kinetic instabilities: electron trapping and release by electrostatic tidal effect
Bibliographic record
Abstract
Abstract Ultra-high resolution particle-in-cell coupled to Monte-Carlo collisions modelling unveils microscale instabilities in non-equilibrium plasmas fulfilling Penrose’s instability criterion. The spontaneous development of ion turbulence in the phase-space generated by charge exchange collisions leads to finite amplitude modulations of the local electric field. The latter are responsible for the trapping of low energy electrons and their transport from the plasma volume to the sheath vicinity. Electrostatic tidal effect occurring near the sheath is responsible for the release of the trapped electrons as a monochromatic bunch, accelerated back towards the source. This instability provides an additional theoretical ground for the anomalous enrichment of low-energy electrons observed by Langmuir probes in similar conditions. The present results demonstrate that marginally fulfilling PIC criteria is insufficient to study the microscale instabilities effects on the electrons dynamics in non-equilibrium low temperature plasmas.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".