Lyα emission in galaxies at <i>z</i> ≃ 5−6: new insight from <i>JWST</i> into the statistical distributions of Lyα properties at the end of reionization
Bibliographic record
Abstract
ABSTRACT JWST has recently sparked a new era of Lyα spectroscopy, delivering the first measurements of the Lyα escape fraction and velocity profile in typical galaxies at z ≃ 6−10. These observations offer new prospects for insight into the earliest stages of reionization. But to realize this potential, we need robust models of Lyα properties in galaxies at z ≃ 5−6 when the IGM is mostly ionized. Here, we use new JWST observations from the JADES and FRESCO surveys combined with VLT/MUSE and Keck/DEIMOS data to characterize statistical distributions of Lyα velocity offsets, escape fractions, and EWs in z ≃ 5−6 galaxies. We find that galaxies with large Lyα escape fractions (>0.2) are common at z ≃ 5−6, comprising 30 per cent of Lyman break selected samples. Comparing to literature studies, our census suggests that Lyα becomes more prevalent in the galaxy population towards higher redshift from z ∼ 3 to z ∼ 6, although we find that this evolution slows considerably between z ∼ 5 and z ∼ 6, consistent with modest attenuation from residual H i in the mostly ionized IGM at z ≃ 5−6. We find significant evolution in Lyα velocity profiles between z ≃ 2−3 and z ≃ 5−6, likely reflecting the influence of resonant scattering from residual intergalactic H i on the escape of Lyα emission near line centre. This effect will make it challenging to use Lyα peak offsets as a probe of Lyman continuum leakage at z ≃ 5−6. We use our z ≃ 5−6 Lyα distributions to make predictions for typical Lyα properties at z ≳ 8 and discuss implications of a recently discovered Lyα emitter at z ≃ 8.5 with a small peak velocity offset (156 km s−1).
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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 | 0.000 |
| 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".