AGE DEPENDENCE OF WIND PROPERTIES FOR SOLAR-TYPE STARS: A 3D STUDY
Bibliographic record
Abstract
ABSTRACT Young and rapidly rotating stars are known for intense, dynamo-generated magnetic fields. Spectropolarimetric observations of those stars in precisely aged clusters are key input for gyrochronology and magnetochronology. We use Zeeman Doppler imaging maps of several young K-type stars of similar mass and radius but with various ages and rotational periods to perform three-dimensional (3D) numerical MHD simulations of their coronae and follow the evolution of their magnetic properties with age. Those simulations yield the coronal structure as well as the instant torque exerted by the magnetized, rotating wind on the star. As stars get older, we find that the angular momentum loss decreases with , which is the reason for the convergence on the Skumanich law. For the youngest stars of our sample, the angular momentum loss shows signs of saturation around , which is a common value used in spin evolution models for K-type stars. We compare these results to semianalytical models and existing braking laws. We observe a complex wind-speed distribution for the youngest stars with slow, intermediate, and fast wind components, which are the result of interaction with intense and nonaxisymmetric magnetic fields. Consequently, in our simulations, the stellar wind structure in the equatorial plane of young stars varies significantly from a solar configuration, delivering insight about the past of the solar system interplanetary medium.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".