The star-forming and ionizing properties of dwarf <i>z</i> ~ 6–9 galaxies in JADES: insights on bursty star formation and ionized bubble growth
Bibliographic record
Abstract
ABSTRACT Reionization is thought to be driven by faint star-forming galaxies, but characterizing this population has long remained very challenging. Here, we utilize deep nine-band JADES (JWST Advanced Deep Extragalactic Survey)/NIRCam (Near-Infrared Camera) imaging to study the star-forming and ionizing properties of 756 $z\sim 6-9$ galaxies, including hundreds of very ultraviolet (UV)-faint objects ($M_\mathrm{UV}\gt -18$). The faintest ($m\sim 30$) galaxies in our sample typically have stellar masses of $M_\ast \sim (1-3)\times 10^7\ \mathrm{ M}_\odot$ and young light-weighted ages ($\sim$50 Myr), though some show strong Balmer breaks implying much older ages ($\sim$500 Myr). We find no evidence for extremely massive galaxies ($\gt 3\times 10^{10}\ \mathrm{ M}_\odot$) in our sample. We infer a strong (factor $\gt $2) decline in the typical [O iii]$+$H $\beta$ equivalent widths (EWs) towards very faint $z\sim 6-9$ galaxies, yet a weak UV luminosity dependence on the H $\alpha$ EWs at $z\sim 6$. We demonstrate that these EW trends can be explained if fainter galaxies have systematically lower metallicities as well as more recently declining star formation histories relative to the most UV-luminous galaxies. Our data provide evidence that the brightest galaxies are frequently experiencing a recent strong upturn in star formation rate. We also discuss how the EW trends may be influenced by a strong correlation between $M_\mathrm{UV}$ and Lyman continuum escape fraction. This alternative explanation has dramatically different implications for the contribution of galaxies along the luminosity function to cosmic reionization. Finally, we quantify the photometric overdensities around two $z\,\gt\,7$ strong Ly $\alpha$ emitters. One Ly $\alpha$ emitter lies close to a strong photometric overdensity, while the other shows no significant nearby overdensity, perhaps implying that not all strong $z\,\gt\, 7$ Ly $\alpha$ emitters reside in large ionized bubbles.
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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 | 0.000 |
| 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".