Evaluating Rotation Periods of M Dwarfs across the Ages
Bibliographic record
Abstract
Abstract In this work we examine M dwarf rotation rates at a range of ages to establish benchmarks for M dwarf gyrochronology. This work includes a sample of 713 spectroscopically classified M0–M8 dwarfs with new rotation rates measured from K2 light curves. We analyze data and recover rotation rates for 179 of these objects. We add these to rotation rates for members of clusters with known ages (5–700 Myr), as well as objects assumed to have field ages (≳1 Gyr). We use Gaia DR2 parallax and ( G – G RP ) photometry to create color–magnitude diagrams to compare objects across samples. We use color–period plots to analyze the period distributions across age, as well as incorporate Hα equivalent width and tangential velocity where possible to further comment on age dependence. We find that the age of transition from rapid to slow rotation in clusters, which we define as an elbow in the period–color plots, depends on spectral type. Later spectral types transition at older ages: M4 for Praesepe at ≈700 Myr, one of the oldest clusters for which M dwarf rotation rates have been measured. The transition from active to inactive Hα equivalent width also occurs at this elbow, as objects transition from rapid rotation to the slowly rotating sequence. Redder or smaller stars remain active at older ages. Finally, using Gaia kinematics we find evidence for rotation stalling for late Ms in the field sample, suggesting the transition happens much later for mid- to late-type M dwarfs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
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".