CONSTRAINING THE Lyα ESCAPE FRACTION WITH FAR-INFRARED OBSERVATIONS OF Lyα EMITTERS
Bibliographic record
Abstract
We study the far-infrared properties of 498 Lyα emitters (LAEs) at z = 2.8, 3.1, and 4.5 in the Extended Chandra Deep Field-South, using 250, 350, and 500 μm data from the Herschel Multi-tiered Extragalactic Survey and 870 μm data from the LABOCA ECDFS Submillimeter Survey. None of the 126, 280, or 92 LAEs at z = 2.8, 3.1, and 4.5, respectively, are individually detected in the far-infrared data. We use stacking to probe the average emission to deeper flux limits, reaching 1σ depths of ∼0.1 to 0.4 mJy. The LAEs are also undetected at ⩾3σ in the stacks, although a 2.5σ signal is observed at 870 μm for the z = 2.8 sources. We consider a wide range of far-infrared spectral energy distributions (SEDs), including an M82 and an Sd galaxy template, to determine upper limits on the far-infrared luminosities and far-infrared-derived star formation rates of the LAEs. These star formation rates are then combined with those inferred from the Lyα and UV emission to determine lower limits on the LAEs' Lyα escape fraction ( f esc (Lyα)). For the Sd SED template, the inferred LAEs f esc (Lyα) are ≳ 30% (1σ) at z = 2.8, 3.1, and 4.5, which are all significantly higher than the global f esc (Lyα) at these redshifts. Thus, if the LAEs f esc (Lyα) follows the global evolution, then they have warmer far-infrared SEDs than the Sd galaxy template. The average and M82 SEDs produce lower limits on the LAE f esc (Lyα) of ∼10%–20% (1σ), all of which are slightly higher than the global evolution of f esc (Lyα), but consistent with it at the 2σ–3σ level.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".