Wrinkles in Time -- I: Rapid Rotators Found in High Eccentricity Orbits
Bibliographic record
Abstract
Recent space-based missions have ushered in a new era of observational astronomy, where high-cadence photometric light curves for thousands to millions of stars in the solar neighborhood can be used to test and apply stellar age-dating methods, including gyrochronology. Combined with precise kinematics, these data allow for powerful new insights into our understanding of the Milky Way's dynamical history. Using TESS data, we build a series of rotation period measurement and confirmation pipelines and test them on 1,560 stars across five benchmark samples: the Pleiades, Pisces--Eridanus, Praesepe, the Hyades, and field stars from the MEarth Project. Our pipelines' recovery rates across these groups are on average 89\%. We then apply these pipelines to 4,085 likely single stars with TESS light curves in two interesting regions of Galactic action space. We identify 141 unique, rapidly rotating stars in highly eccentric orbits in the disk, some of which appear as rotationally young as the 120-Myr-old Pleiades. Pending spectroscopic analysis to confirm their youth, this indicates these stars were subject to fast-acting dynamical phenomena, the origin of which will be investigated in later papers in this series.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".