Kinetic Modeling of Inertial Alfvén Waves in the Solar Corona: Implications for Heating and Particle Acceleration
Bibliographic record
Abstract
Recent observations from NASA’s Parker Solar Probe (PSP) and ESA’s Solar Orbiter high light the importance of Alfvén waves in solar coronal heating and accelerating the solar wind. In this study, we investigate inertial Alfvén waves (IAWs), which operate at electron inertial scales, as a potential mechanism for plasma heating and charged particle acceleration in the low solar corona (0 - 10 RSun). Using kinetic plasma theory within a non-Maxwellian (Cairns) distribution framework, we evaluate the perturbed electromagnetic (EM) field ratios and demonstrate their strong dependence on the non-thermal parameter Λ. These field ratios inform the computation of Poynting flux, revealing that for Λ > 0, IAWs can efficiently channel energy over extended distances (RSun) along the magnetic field B while rapidly dissipating energy across it. We further assess the net power carried by IAWs in coronal flux tube loops and show enhanced power transport at larger normalized electron inertial scales (c k⊥/ωpe). The parallel and perpendicular electric potentials associated with IAWs, both shaped by Λ, indicate that wave energy is transferred to particles via damping, leading to effective heating. By evaluating net resonant particle speeds, we find that energy deposition occurs preferentially along the magnetic field lines. Additionally, we show that both the group velocity and damping length of IAWs increase with stronger non-thermal features. These results underscore the role of IAWs in coronal heating and particle acceleration in the inherently non-Maxwellian solar corona.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".