Observations of Spin-down in Post-mass-transfer Stars and the Possibility for Blue Straggler Gyrochronology
Bibliographic record
Abstract
Abstract Blue stragglers and other mass transfer/collision products are likely born with rapid rotation rates due to angular momentum transfer during mass-transfer, merger, or collisional formation. However, less is known about the angular momentum evolution of these stars as they age. Here we compare rotation rates and post-formation ages of mass-transfer products to models of angular momentum evolution for normal main-sequence (MS) stars and collisionally formed blue stragglers. In our sample, we include both F- and G-type blue stragglers in the cluster NGC 188 and post-mass-transfer GK MS stars in the field, all binaries with white dwarf (WD) companions. We compare ages derived from WD cooling models to photometric rotation periods and/or spectral v sin i measurements. We demonstrate that these systems have rapid rotation rates soon after formation. They then spin down as they age, much like standard solar-type MS stars do. We discuss the physical implications of this result, which suggests that the spin-down of post-mass transfer stars can be described by standard magnetic-braking prescriptions. This opens up the possibility of using gyrochronology as a method to determine the time since formation of blue straggler stars and other post-mass-transfer binaries.
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 | 0.000 |
| 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".