Globular Clusters with Dark Matter Halos. II. Evolution in a Tidal Field
Bibliographic record
Abstract
In this second paper in our series, we continue to test primordial scenarios of globular cluster formation, which predict that globular clusters formed in the early universe in the potential of dark matter minihalos. In this paper we use high-resolution N -body simulations to model tidal stripping experienced by primordial dark matter-dominated globular clusters in the static gravitational potential of the host dwarf galaxy. We test both cuspy Navarro-Frenk-White (NFW) and flat-core Burkert models of dark matter halos. Our primordial globular cluster with an NFW dark matter halo survives severe tidal stripping and after 10 orbits is still dominated by dark matter in its outskirts. Our cluster with a Burkert dark matter halo loses almost all its dark matter to tidal stripping and starts losing stars at the end of our simulations. The results of this paper reinforce our conclusion in Paper I that current observations of globular clusters are consistent with the primordial picture of globular cluster formation.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".