Solar coronal heating: role of kinetic and inertial Alfvén waves in heating and charged particle acceleration
Bibliographic record
Abstract
ABSTRACT A comprehensive understanding of solar coronal heating and charged particle acceleration remains one of the most critical challenges in space and astrophysical plasma physics. In this study, we explore the contribution of Alfvén waves – both in their kinetic (KAWs) and inertial (IAWs) regimes – to particle acceleration and solar coronal heating. Employing a kinetic plasma framework in the generalized Vlasov–Maxwell model, we analyse the dynamics of these waves with a focus on the perpendicular (i.e. across the magnetic field lines) Poynting flux vectors and the net resonant speed of the particles. We found the Poynting flux of KAWs decays rapidly, indicating short-range energy transport, while IAWs exhibit slower decay, enabling energy transfer over larger distances (R$_{\text{Sun}}$) in the solar corona. We also evaluate the electric potentials associated with KAWs and IAWs and find the KAW’s potentials are significantly enhanced at larger wavenumbers ($k_x \rho _i>0.1$) regimes, while IAWs exhibit reduced parallel and enhanced perpendicular electric potentials, governed by the perturbed electric fields (${E_x}$ and ${E_z}$) values. Additionally, we determine the net resonant speed of particles in the perpendicular direction and demonstrate that these wave–particle interactions can efficiently heat the solar corona over extended distances R$_{\text{Sun}}$. Finally, we quantify the power transported by KAWs and IAWs through solar flux loop tubes, finding that both wave types deliver greater energy with increasing ${T_e/T_i}$ and $c k_x/\omega _{pe}$ values. These insights not only deepen our theoretical understanding of wave-driven heating mechanisms but also provide valuable implications for interpreting solar wind, corona, heliospheric, and magnetospheric dynamics.
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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 | 0.000 |
| 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 | 0.000 |
| 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".