VELOCITY VARIATIONS IN THE PHOENIX–HERMUS STAR STREAM
Bibliographic record
Abstract
ABSTRACT Measurements of velocity and density perturbations along stellar streams in the Milky Way provide a time-integrated measure of dark matter substructure at larger galactic radius than the complementary instantaneous inner-halo strong lensing detection of dark matter sub-halos in distant galaxies. An interesting case to consider is the proposed Phoenix–Hermus star stream, which is long, thin, and on a nearly circular orbit, making it a particular good target to study for velocity variations along its length. In the presence of dark matter sub-halos, the stream velocities are significantly perturbed in a manner that is readily understood with the impulse approximation. A set of simulations shows that only sub-halos above a few 107 M ⊙ lead to reasonably long-lived observationally detectable velocity variations of amplitude of order 1 km s−1, with an average of about one visible hit per (two-armed) stream over a 3 Gyr interval. An implication is that globular clusters themselves will not have a visible impact on the stream. Radial velocities have the benefit of being completely insensitive to distance errors. Distance errors scatter individual star velocities perpendicular and tangential to the mean orbit, but their mean values remain unbiased. Calculations like these help build the quantitative case to acquire large, fairly deep, precision velocity samples of stream stars.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".