Bibliographic record
Abstract
Abstract Dark matter subhalos that pass a thin tidal star stream change the velocities of the stars near the point of closest encounter. Subsequent orbital evolution increases the stream width and spreads the changes along the stream. We measure the average widths and velocity dispersions of stream populations in three Milky Way–like cold dark matter cosmology simulations containing star particle globular clusters and galactic disks of 0, 1, and 2 times a baseline model. Power-law fits to the velocity dispersion with stream longitude, ϕ, for the overlaid streams in the 10–60 kpc range find σ ≃ 5–15 ϕ 0.2–0.5 km s−1, with the coefficients depending on the subhalo numbers, as well as the stream measurement details. The velocity distributions summed along the entire length of the streams do not require the progenitor location. They also rise with subhalo number and are significantly non-Gaussian, with the ratios of the 6σ to the 3σ clipped velocity dispersions being ∼1.5 ± 0.3 and ∼2.5 ± 1 for measurements within 1° and 5° of the streams, respectively. Streams longer than 50° have an average radial velocity dispersion of 2.1 km s−1 with a disk and 4.2 km s−1 without a disk. However, a few similar thin, low-velocity dispersion streams are present in all three simulations. Statistically reliable conclusions require velocity data extending several degrees from the stream centerline for a set of streams.
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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 | 0.001 |
| 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".