Minihalo photoevaporation during cosmic reionization: evaporation times and photon consumption rates
Bibliographic record
Abstract
The weak, R-type ionization fronts (I-fronts) which swept across the intergalactic medium (IGM) during the reionization of the universe often found their paths blocked by cosmological minihaloes. When this happened, the neutral gas which filled each minihalo was photoevaporated; as the I-front burned its way through the halo, decelerating from R-type to D-type, all the gas was blown back into the IGM as an ionized, supersonic wind. In a previous paper (Shapiro, Iliev and Raga 2004), we described this process and presented our results of the first simulations of it by numerical gas dynamics with radiation transport in detail. For illustration we focused on the particular case of a 10^7 solar masses minihalo overrun at z=9 by an intergalactic I-front caused by a distant source of ionizing radiation, for different source spectra (either stellar from massive Pop. II or III stars, or QSO-like) and a flux level typical of that expected during reionization. In a LambdaCDM universe, minihaloes formed in abundance before and during reionization and, thus, their photoevaporation is an important, possibly dominant, feature of reionization, which slowed it down and wasted ionizing photons. We have now performed a larger set of high-resolution simulations to determine and quantify the dependence of minihalo photoevaporation times and photon consumption rates on halo mass, redshift, ionizing flux level and spectrum. We find that the average number of ionizing photons each minihalo atom absorbs during its photoevaporation is typically in the range 2-10. For the collapsed fraction in minihaloes expected during reionization, this can add about 1 photon per total atom to the requirements for completing reionization, potentially doubling the minimum number of photons required to reionize the universe.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".