A 4 Gyr M-dwarf Gyrochrone from CFHT/MegaPrime Monitoring of the Open Cluster M67
Bibliographic record
Abstract
Abstract We present stellar rotation periods for late K- and early M-dwarf members of the 4 Gyr old open cluster M67 as calibrators for gyrochronology and tests of stellar spin-down models. Using Gaia EDR3 astrometry for cluster membership and Pan-STARRS (PS1) photometry for binary identification, we build this set of rotation periods from a campaign of monitoring M67 with the Canada–France–Hawaii Telescope’s MegaPrime wide-field imager. We identify 1807 members of M67, of which 294 are candidate single members with significant rotation period detections. Moreover, we fit a polynomial to the period versus color-derived effective temperature sequence observed in our data. We find that the rotation of very cool dwarfs can be explained by simple solid-body spin-down between 2.7 and 4 Gyr. We compare this rotational sequence to the predictions of gyrochronological models and find that the best match is Skumanich-like spin-down, P rot ∝ t 0.62, applied to the sequence of Ruprecht 147. This suggests that, for spectral types K7–M0 with near-solar metallicity, once a star resumes spinning down, a simple Skumanich-like relation is sufficient to describe their rotation evolution, at least through the age of M67. Additionally, for stars in the range M1–M3, our data show that spin-down must have resumed prior to the age of M67, in conflict with the predictions of the latest spin-down models.
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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 | 0.001 | 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".