The ionizing photon production efficiency at <i>z</i> ∼ 6 for Lyman-alpha emitters using JEMS and MUSE
Bibliographic record
Abstract
ABSTRACT We study the ionizing photon production efficiency at the end of the Epoch of Reionization (z ∼ 5.4 − 6.6) for a sample of 30 Ly α emitters. This is a crucial quantity to infer the ionizing photon budget of the universe. These objects were selected to have reliable spectroscopic redshifts, assigned based on the profile of their Ly α emission line, detected in the MUSE deep fields. We exploit medium-band observations from the JWST Extragalactic Medium-band Survey (JEMS) to find the flux excess corresponding to the redshifted Hα emission line. We estimate the ultraviolet (UV) luminosity by fitting the full JEMS photometry, along with several HST photometric points, with Prospector. We find a median UV continuum slope of $\beta = -2.09^{+0.23}_{-0.21}$, indicating young stellar populations with little-to-no dust attenuation. Supported by this, we derive ξion,0 with no dust attenuation and find a median value of log$\frac{\xi _{ion,0}}{\text{Hz erg}^{-1}} = 25.44^{+0.21}_{-0.15}$. If we perform dust attenuation corrections and assume a Calzetti attenuation law, our values are lowered by ∼0.1 dex. Our results suggest Ly α emitters at the Epoch of Reionization have slightly enhanced ξion,0 compared to previous estimations from literature, in particular, when compared to the non-Ly α emitting population. This initial study provides a promising outlook on the characterization of ionizing photon production in the early universe. In the future, a more extensive study will be performed on the entire data set provided by the JWST Advanced Deep Extragalactic Survey (JADES). Thus, for the first time, allowing us to place constraints on the wider galaxy populations driving reionization.
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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 | 0.001 |
| 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 | 0.000 |
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".