Masses and scaling relations for nuclear star clusters, and their co-existence with central black holes
Bibliographic record
Abstract
Galactic nuclei typically host either a nuclear star cluster (NSC, prevalent in galaxies with masses ≲1010 M⊙) or a massive black hole (MBH, common in galaxies with masses ≳1012 M⊙). In the intermediate-mass range, some nuclei host both an NSC and an MBH. In this paper, we explore scaling relations between NSC mass (|${\cal M}_{\rm NSC}$|) and host-galaxy total stellar mass (|${\cal M}_{\star ,\rm gal}$|) using a large sample of NSCs in late- and early-type galaxies, including a number of NSCs harbouring an MBH. Such scaling relations reflect the underlying physical mechanisms driving the formation and (co)evolution of these central massive objects. We find ∼1.5σ significant differences between NSCs in late- and early-type galaxies in the slopes and offsets of the relations reff,NSC–|${\cal M}_{\rm NSC}$|, reff,NSC–|${\cal M}_{\star ,\rm gal}$| and |${\cal M}_{\rm NSC}$|–|${\cal M}_{\star ,\rm gal}$|, in the sense that (i) NSCs in late types are more compact at fixed |${\cal M}_{\rm NSC}$| and |${\cal M}_{\star ,\rm gal}$|; and (ii) the |${\cal M}_{\rm NSC}$|–|${\cal M}_{\star ,\rm gal}$| relation is shallower for NSCs in late types than in early types, similar to the |${\cal M}_{\rm BH}$|–|${\cal M}_{\star ,\rm bulge}$| relation. We discuss these results in the context of the (possibly ongoing) evolution of NSCs, depending on host-galaxy type. For NSCs with an MBH, we illustrate the possible influence of an MBH on its host NSC, by considering the ratio between the radius of the MBH sphere of influence and reff,NSC. NSCs harbouring a sufficiently massive black hole are likely to exhibit surface brightness profile deviating from a typical King profile.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".