Inside the bubble: exploring the environments of reionisation-era Lyman-<i>α</i> emitting galaxies with JADES and FRESCO
Bibliographic record
Abstract
We present a study of the environments of 17 Lyman- α emitting galaxies (LAEs) in the reionisation-era (5.8 < z < 8) identified by JWST/NIRSpec as part of the JWST Advanced Deep Extragalactic Survey (JADES). Unless situated in sufficiently (re)ionised regions, Lyman- α emission from these galaxies would be strongly absorbed by neutral gas in the intergalactic medium (IGM). We conservatively estimate sizes of the ionised regions required to reconcile the relatively low Lyman- α velocity offsets (Δ v Ly α < 300 km s −1 ) with moderately high Lyman- α escape fractions ( f esc, Ly α > 5%) observed in our sample of LAEs, suggesting the presence of ionised hydrogen along the line of sight towards at least eight out of 17 LAEs. We find minimum physical ‘bubble’ sizes of the order of R ion ∼ 0.1–1 pMpc are required in a patchy reionisation scenario where ionised bubbles containing the LAEs are embedded in a fully neutral IGM. Around half of the LAEs in our sample are found to coincide with large-scale galaxy overdensities seen in FRESCO at z ∼ 5.8–5.9 and z ∼ 7.3, suggesting Lyman- α transmission is strongly enhanced in such overdense regions, and underlining the importance of LAEs as tracers of the first large-scale ionised bubbles. Considering only spectroscopically confirmed galaxies, we find our sample of UV-faint LAEs ( M UV ≳ −20 mag) and their direct neighbours are generally not able to produce the required ionised regions based on the Lyman- α transmission properties, suggesting lower-luminosity sources likely play an important role in carving out these bubbles. These observations demonstrate the combined power of JWST multi-object and slitless spectroscopy in acquiring a unique view of the early Universe during cosmic reionisation via the most distant LAEs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".