THE FIRST MASSIVE BLACK HOLE SEEDS AND THEIR HOSTS
Bibliographic record
Abstract
We investigate the formation of the first massive black holes (MBHs) in high redshift galaxies, with the goal of providing insights to which galaxies do or do not host MBHs. We adopt a novel approach to forming seed black holes in galaxy halos in cosmological SPH+ N -body simulations. The formation of MBH seeds is dictated directly by the local gas density, temperature, and metallicity, and motivated by physical models of MBH formation. We explore seed black hole populations as a function of halo mass and redshift, and examine how varying the efficiency of MBH seed formation affects the relationship between black holes and their hosts. Seed black holes tend to form in halos with mass between 10 7 and 10 9 M ☉ , and the formation rate is suppressed around z = 5 due to the diffusion of metals throughout the intergalactic medium. We find that the time of MBH formation and the occupation fraction of black holes are a function of the host halo mass. By z = 5, halos with mass M halo > 3 × 10 9 M ☉ host MBHs regardless of the efficiency of seed formation, while the occupation fraction for smaller halos increases with black hole formation efficiency. Our simulations explain why MBHs are found in some bulgeless and dwarf galaxies, but we also predict that their occurrence becomes rarer and rarer in low-mass systems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".