Lyman-alpha emitters and the 21 cm power spectrum as probes of density–ionization correlation in the epoch of reionization
Bibliographic record
Abstract
ABSTRACT Due to the large cross-section of Ly α photons with hydrogen, Lyman-alpha emitters (LAEs) are sensitive to the presence of neutral hydrogen in the intergalactic medium (IGM) during the epoch of reionization (EoR): the period in the Universe’s history where neutral hydrogen in the IGM is ionized. The type of correlation between the ionized regions of the IGM with respect to the underlying intrinsic LAEs has a pronounced effect on the number of observed LAEs and their apparent clustering. As a result, observations of LAEs during the EoR can be used as a probe of the EoR morphology. Here, we build on previous works where we parametrize the density–ionization correlation during the EoR, and study how the observed number density and angular correlation function (ACF) of LAEs depend on this parametrization. Using Subaru measurements of the number density of LAEs and their ACF at z = 6.6, we place constraints on the EoR morphology. We find that measurements of LAEs at z = 6.6 alone cannot distinguish between different density–ionization models at $68{{\ \rm per\ cent}}$ credibility. However, adding information regarding the number density, and ACF, of LAEs at z = 6.6 to 21 cm power spectrum measurements using the hydrogen Epoch of Reionization Array at the mid-point of reionization can rule out uncorrelated and outside-in reionization at $99{{\ \rm per\ cent}}$ credibility.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".