The Binary Fraction of Stars in Dwarf Galaxies: The Cases of Draco and Ursa Minor
Bibliographic record
Abstract
Abstract Measuring the frequency of binary stars in dwarf spheroidal galaxies (dSphs) requires data taken over long time intervals. We combine radial velocity measurements from five literature sources taken over the course of ∼30 years to yield the largest multi-epoch kinematic sample for stars in the dSphs Draco and Ursa Minor. With this data set, we are able to implement an improved version of the Bayesian technique described in Spencer et al. to evaluate the binary fraction of red giant stars in these dwarf galaxies. Assuming Duquennoy & Mayor period and mass ratio distributions, the binary fractions in Draco and Ursa Minor are and , respectively. We find that a normal mass ratio distribution is preferred over a flat distribution, and that log-normal period distributions centered on long periods ( ) are preferred over distributions centered on short ones. We reanalyzed the binary fractions in Leo II, Carina, Fornax, Sculptor, and Sextans, and find that there is <1% chance that binary fraction is a constant quantity across all seven dwarfs, unless the period distribution varies greatly. This indicates that the binary populations in Milky Way dSphs are not identical in regard to their binary fractions, period distributions, or both. We consider many different properties of the dwarfs (e.g., mass, radius, luminosity, etc.) and find that binary fraction might be larger in dwarfs that formed their stars quickly and/or have high velocity dispersions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".