The effects of population III radiation backgrounds on the cosmological 21-cm signal
Bibliographic record
Abstract
ABSTRACT We investigate the effects of Population III (Pop III) stars and their remnants on the cosmological 21-cm global signal. By combining a semi-analytic model of Pop III star formation with a global 21-cm simulation code, we investigate how X-ray and radio emission from accreting Pop III black holes may affect both the timing and depth of the 21-cm absorption feature that follows the initial onset of star formation during the Cosmic Dawn. We compare our results to the findings of the EDGES experiment, which has reported the first detection of a cosmic 21-cm signal. In general, we find that our fiducial Pop III models, which have peak star formation rate densities of ∼10−4 M⊙ yr−1 Mpc−3 between z ∼ 10 and z ∼ 15, are able to match the timing of the EDGES signal quite well, in contrast to models that ignore Pop III stars. To match the unexpectedly large depth of the EDGES signal without recourse to exotic physics, we vary the parameters of emission from accreting black holes (formed as Pop III remnants) including the intrinsic strength of X-ray and radio emission as well as the local column density of neutral gas. We find that models with strong radio emission and relatively weak X-ray emission can self-consistently match the EDGES signal, though this solution requires fine-tuning. We are only able to produce signals with sharp features similar to the EDGES signal if the Pop III IMF is peaked narrowly around $140 \, \mathrm{M}_\odot$.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".