Flaring together: A preferred angular separation between sympathetic flares on the Sun
Bibliographic record
Abstract
Context. Sympathetic solar flares are eruptions that occur nearby in space and time, driven by an apparent interaction between the active regions in which they are triggered. Their statistical existence on the Sun has yet to be firmly established. Aims. The main goal of this paper is to identify a statistical signature of sympathetic flares, characterize their properties, and determine a potential mechanism driving their interaction. Methods. We performed a statistical analysis of a large number of flares observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO), the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI), and the Spectrometer Telescope for Imaging X-rays (STIX) on Solar Orbiter during solar cycle 24 and 25. We examined the spatiotemporal distribution of consecutive flare pairs across solar cycle phases and hemispheres along with the propagation velocity of potential causal interactions and the relationship between flare magnitudes. Results. We observed an excess of hemispheric flares separated by about 30° of longitude and triggered in less than 1.5 hours from each other. This peak in angular separation varies with the solar cycle phase and hemisphere. Moreover, we identified a deficit of transequatorial events separated by 25−30° in latitude and less than 5° in longitude, a phenomenon we term unsympathetic flares. Conclusions. We provide strong statistical evidence for the existence of sympathetic flares on the Sun, demonstrating that their occurrence rate reaches approximately 5% across the three instruments used in this study. Additionally, we propose an interpretation of the observed angular scale of the sympathetic phenomenon based on the separation between magnetic field line footpoints derived from potential field source surface extrapolations.
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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 | 0.003 |
| 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".