JADES reveals a large population of low-mass black holes at high redshift
Bibliographic record
Abstract
ABSTRACT James Webb Space Telescope (JWST) has revealed a large population of active galactic nuclei (AGNs) in the distant Universe, which are challenging our understanding of early massive black hole (BH) seeding and growth. We expand the exploration of this population to lower luminosities by stacking $\sim$600 NIRSpec grating spectra from the JWST Advanced Deep Extragalactic Survey (JADES) at $3< z < 7$, in bins of redshift, [O iii]5007 luminosity and equivalent width, UV luminosity, and stellar mass. In multiple stacks, we detect a broad component of H $\alpha$ without a counterpart in [O iii], implying that it is not due to outflows but traces the broad-line region of a large population of low-luminosity AGNs not detected in individual spectra. The detection, in some stacks, of high [O iii]4363/H $\gamma$, typical of AGNs, further confirms the detection of a large population of AGNs. We infer that the stacks probe BHs with masses of a few times $10^{6} {\rm M}_{\odot }$ accreting at rates $L/L_{Edd}$$\sim$ 0.02–0.1, i.e. a low-mass and dormant parameter space poorly explored by previous studies on individual targets. We identify populations of BHs that fall within the scatter of the local $M_{BH}\!-\!M_{*}$ scaling relation, indicating that there is a population of high-z BHs that are not overmassive relative to their host galaxies. Yet, on average, the stacks are still overmassive relative the local relation, with some of them 1–2 dex above it. We infer that the BH mass function at $3< z < 5$ is consistent with models in which BHs evolve through short bursts of super-Eddington accretion.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".