The Impact of Small‐Scale Structure on Cosmological Ionization Fronts and Reionization
Bibliographic record
Abstract
The propagation of cosmological ionization fronts during the reionization of the universe is strongly influenced by small-scale gas inhomogeneities due to structure formation. These inhomogeneities include both collapsed minihalos, which are generally self-shielding, and lower density structures, which are not. The minihalos are dense and sufficiently optically thick to trap intergalactic ionization fronts, blocking their path and robbing them of ionizing photons until the minihalo gas is expelled as an evaporative wind. The lower density structures do not trap these fronts, but they can slow them down by increasing the overall recombination rate in the intergalactic medium (IGM). In this paper we study the effects of both types of inhomogeneities, including nonlinear clustering effects, and we find that both IGM clumping and collapsed minihalos have significant yet qualitatively different impacts on reionization. While the number density of minihalos on average increases strongly with time, the density of minihalos inside H II regions around ionizing sources is largely constant. Thus the impact of minihalos is essentially to decrease the number of ionizing photons available to the IGM at all epochs, which is equivalent to a reduction in the luminosity of each source. On the other hand, the effect of IGM clumping increases strongly with time, slowing down reionization and extending it. Thus while the impact of minihalos is largely degenerate with the unknown source efficiency, IGM clumping can help significantly in reconciling the recent observations of cosmic microwave background polarization with quasar absorption spectra at z ~ 6, which together point to an early but extended reionization epoch.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".