Warm plasma effects on electromagnetic ion cyclotron wave MeV electron interactions in the magnetosphere
Bibliographic record
Abstract
[1] The full kinetic linear dispersion relation in a warm plasma with He+ and O+ ions is used to estimate the minimum resonant electron energies required for resonant scattering of relativistic electrons by electromagnetic ion cyclotron waves. We find two significant differences from the cold-plasma approximation: (1) waves can be excited inside the stop bands and at ion gyrofrequencies for relatively small wave numbers k < Ωp/vA and (2) short wavelengths with k > Ωp/vA experience strong cyclotron damping. We show that, in general, minimum resonant energy of electrons Emin depends only on the wave number k, magnetic field strength B, and plasma mass density ρ and depends on the wave frequency ω only implicitly, via the dispersion relation. Formulae for Emin as function of ω based on cold-plasma approximation predict the lowest energy loss where ω → since in this approximation k → ∞ at these frequencies. We show this inference is incorrect and that kinetic effects mean that the ion gyrofrequencies are no longer necessarily preferential for low energy loss. The lowest values of Emin are obtained where the dispersion supports the largest wave numbers k and in the regions of the largest mass densities ρ and the lowest magnetic fields B. For realistic magnetospheric conditions Emin ∼ 2 MeV and can only drop to ∼500 keV inside dense plasmaspheric plumes, with plasma density of the order of 500 cm−3, or during plasmaspheric expansions to high L shells (L ∼ 7).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".