Age dependence of Lyα escape fraction of Lyα emitters and their significant role in cosmic reionization
Bibliographic record
Abstract
Abstract We study the Lyα escape fraction, $f_{\mathrm{esc}}^{\mathrm{Ly\alpha }}$of Lyα emitters (LAEs) identified by Subaru/HSC narrowband imaging at z = 2.2-6.6, using publicly available deep imaging data from HST and JWST. We perform SED fitting for 127 LAEs at 0.4 − 5.0 μm to estimate their physical properties robustly, and confirm that two distinct LAE populations exist: young LAEs (< 100 Myr) and old LAEs (> 100 Myr). Young LAEs are characterized by burst-like star formation activity and low dust content, significantly differing from Lyman-break galaxies (LBGs) at the same stellar mass, while old LAEs show similar star formation activity to LBGs, yet with lower dust content and more compact morphology in rest-UV/optical than LBGs. The $f_{\mathrm{esc}}^{\mathrm{Ly\alpha }}$of LAEs is anticorrelated with stellar mass, and this correlation is found to depend on the age of LAEs, such that old LAEs show a weaker anticorrelation than young LAEs, and tend to exhibit higher $f_{\mathrm{esc}}^{\mathrm{Ly\alpha }}$than young LAEs at a given stellar mass. This implies that Lyα photons escape more efficiently from old LAEs, possibly through the low-density channels of H i and dust created by outflows. The average $f_{\mathrm{esc}}^{\mathrm{Ly\alpha }}$of young LAEs remains nearly constant at ∼40% at z = 2.2 − 6.6, suggesting that the previously observed evolution of global $f_{\mathrm{esc}}^{\mathrm{Ly\alpha }}$of star-forming galaxies (SFGs) is due to the changes in the LAE fraction among the SFGs. Converting $f_{\mathrm{esc}}^{\mathrm{Ly\alpha }}$to Lyman continuum escape fraction using empirical relations, we demonstrate that LAEs alone can supply the ionizing photons necessary for reionization at z ∼ 6, causing rapid and late reionization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".