JADES: measuring reionization properties using Lyman-alpha emission
Bibliographic record
Abstract
ABSTRACT Ly$\alpha$ is the transition to the ground state from the first excited state of hydrogen (the most common element). Resonant scattering of this line by neutral hydrogen greatly impedes its emergence from galaxies, so the fraction of galaxies emitting Ly$\alpha$ is a tracer of the neutral fraction of the intergalactic medium (IGM), and thus the history of reionization. In previous works, we used early JWST/NIRSpec data from the JWST Advanced Deep Extragalactic Survey (JADES) to classify and characterize Ly$\alpha$ emitting galaxies (LAEs). This survey is approaching completion, and the current sample is nearly an order of magnitude larger. From a sample of 795 galaxies in JADES at $4.0\lt z\lt 14.3$, we find evidence for Ly$\alpha$ emission in 150 sources. We reproduce the previously found correlation between Ly$\alpha$ escape fraction ($f\rm _{esc}^{Ly\alpha }$) – Ly$\alpha$ rest-frame equivalent width (${\rm REW}_{\rm Ly\alpha }$) and the negative correlation between Ly$\alpha$ velocity offset – $f\rm _{esc}^{Ly\alpha }$. Both $f\rm _{esc}^{Ly\alpha }$ and ${\rm REW}_{\rm Ly\alpha }$ decrease with redshift ($z\gtrsim 5.5$), indicating the progression of reionization on a population scale. Our data are used to demonstrate an increasing IGM transmission of Ly$\alpha$ from $z\sim 14-6$. We measure the completeness-corrected fraction of LAEs ($X\rm _{Ly\alpha }$) from $z=4-9.5$. An application of these $X\rm _{Ly\alpha }$ values to the results of previously utilized semi-analytical models suggests a high neutral fraction at $z=7$ (${X_{\rm HI}}\sim 0.8-0.9$). Using an updated fit to the intrinsic distribution of ${\rm REW}_{\rm Ly\alpha }$ results in a lower value in agreement with current works (${X_{\rm HI}}= 0.64_{-0.21}^{+0.13}$). This sample of LAEs will be paramount for unbiased population studies of galaxies in the EoR.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
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".