Star Stream Velocity Distributions in Cold Dark Matter and Warm Dark Matter Galactic Halos
Bibliographic record
Abstract
Abstract The dark matter subhalos orbiting in a galactic halo perturb the orbits of stars in thin stellar streams. Over time, the random velocities in the streams develop non-Gaussian wings. The rate of velocity increase is approximately a random walk at a rate proportional to the number of subhalos, primarily those in the mass range ≈10 6−7 M ⊙ . The distribution of random velocities in long streams is measured in simulated Milky Way–like halos that develop in representative warm dark matter (WDM) and cold dark matter (CDM) cosmologies. The radial velocity distributions are well modeled as the sum of a Gaussian and an exponential. The resulting Markov Chain Monte Carlo fits find Gaussian cores of 1−2 km s −1 and exponential wings that increase from 3 km s −1 for 5.5 keV WDM, 4 km s −1 for 7 keV WDM, to 6 km s −1 for a CDM halo. The observational prospects to use stream measurements to constrain the nature of galactic dark matter are discussed.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".