A solar rotation signature in cosmic dust observed in STEREO spacecraft data
Bibliographic record
Abstract
Aims. Cosmic dust within the Solar System is subject to a range of forces that can modify its trajectory, including gravity, radiation pressure, and the Lorentz force. Lorentz force interactions between the solar wind and dust arise due to the motion of charged dust grains with respect to the solar wind plasma flow and the magnetic fields carried by that flow. For dust grains where the charge to mass ratio is sufficiently large, the Lorentz force can significantly modify the dust grain motion. At the same time, properties of the magnetic fields and plasma in the solar wind are modulated by solar periodicities, such as the 11-year solar cycle and the solar rotation period. These solar periodicities are therefore expected to be imparted onto the trajectories of dust moving within the Solar System via Lorentz force interactions. Methods. We examined nearly two decades of cosmic dust observations made by the twin STEREO spacecraft at 1 AU for periodicities in the dust flux. We created a two-dimensional toy model to examine whether it is reasonable to expect solar-rotation variability in solar wind magnetic field and plasma velocities to modify the trajectories of dust that reaches 1 AU. Results. Periodic modulations of the dust flux observed by STEREO at 1 AU are identified near the solar rotation period and its harmonics. The toy model suggests that solar-rotation variability of the solar wind can be sufficient to alter the trajectories of some dust within the Solar System.
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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 | 0.001 | 0.001 |
| 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".