Modeling the properties of guided poloidal Alfvén waves with finite asymmetric ionospheric conductivities in a dipole field
Bibliographic record
Abstract
Analytical and numerical solutions to the guided poloidal Alfvén wave equation in a dipole field are developed, including the effects of realistic and asymmetric finite ionospheric conductivities. We show that when the ionospheric Pedersen conductivity in one hemisphere is less than a critical value, then quarter‐wavelength harmonic modes become possible. We present solutions using realistic plasma density variations along the field line and illustrate how the electric and magnetic fields of a field‐aligned half‐wavelength harmonic mode change as the ionospheric conductivities are made increasingly asymmetric and the wave develops into a quarter‐wavelength mode. Further, we show how over a small critical range of ionospheric Pedersen conductivities, the wave damping rates and frequencies change rapidly as this transition from half‐ to quarter‐wavelength mode occurs. We also show that the phase difference between the electric and magnetic field components is strongly dependent upon the distance along the magnetic field line, upon the asymmetry in the ionospheric Pedersen conductivities, and significantly upon which hemisphere has its footprint in the ionosphere whose conductivity is close to critical. This has important implications for inferring the field‐aligned harmonic mode of standing ULF pulsations when using single satellite data.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".