SED Analysis of 13 Spectroscopically Confirmed Galaxies at z$\simeq$6 to Constrain UV-Slope, Model Dust Attenuation and Escape Fractions
Bibliographic record
Abstract
The reionization of the hydrogen in the Universe is thought to have completed by redshift $z\simeq5.5-6$. To probe this era, galaxy observations in the Subaru Deep Field (SDF) have identified more than 100 galaxies at $z\simeq6$, many spectroscopically confirmed through follow-up observations. We model the spectral energy distributions (SEDs) of 13 SDF galaxies with the CIGALE and Dense Basis codes using available optical/IR data. Modeling deep IR photometry has the potential to constrain the galaxy's Lyman continuum (LyC) escape fraction (\fesc). We use the modeled nebular emission lines and find that the implied escape fractions ranges from \textbf{0 to 0.8 with a median of $\sim$0.35 for Dense Basis and $\sim$0.55 for CIGALE.} Significant uncertainties in the data exist, so that fitting results in a large range of \fesc\ for individual objects. The implied median \fesc-values may be high enough for galaxies to finish reionization by $z\sim6$. Furthermore, we find no strong trends between the UV-slope $β$ or \EBminV with model \fesc. If true, the lack of trends suggest that other factors besides nebular emission or dust extinction could have led to LyC escaping, such as the presence of holes in the ISM with sufficiently wide opening angles from outflows of supernovae and/or weak AGN, resulting in a range of implied \fesc-values depending on the viewing angle of each galaxy. The current \textit{HST, Spitzer} and ground-based photometric and model errors for the galaxies remain large, so IR spectroscopic observations with the \textit{James Webb Space Telescope} are needed to constrain this possibility.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".