Dark matter cores in massive high-<i>z</i> galaxies formed by baryonic clumps
Bibliographic record
Abstract
ABSTRACT The rotation curves of some star-forming massive galaxies at redshift two decline over the radial range of a few times the effective radius, indicating a significant deficit of dark matter (DM) mass in the galaxy centre. The DM mass deficit is interpreted as the existence of a DM density core rather than the cuspy structure predicted by the standard cosmological model. A recent study proposed that a galaxy merger, in which the smaller satellite galaxy is significantly compacted by dissipative contraction of the galactic gas, can heat the centre of the host galaxy and help make a large DM core. By using an N-body simulation, we find that a large amount of DM mass is imported to the centre by the merging satellite, making this scenario an unlikely solution for the DM mass deficit. In this work, we consider giant baryonic clumps in high-redshift galaxies as alternative heating source for creating the baryon dominated galaxies with a DM core. Due to dynamical friction, the orbit of clumps decays in a few Gyr and the baryons condensate at the galactic centre. As a back-reaction, the halo centre is heated up and the density cusp is flattened out. The combination of the baryon condensation and core formation makes the galaxy baryon dominated in the central 2–5 kpc, comparable to the effective radius of the observed galaxies. Thus, the dynamical heating by giant baryonic clumps is a viable mechanism for explaining the observed dearth of DM in high redshift galaxies.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".