Cosmic Reionization On Computers: Biases and Uncertainties in the Measured Mean Free Path at the End Stage of Reionization
Bibliographic record
Abstract
Recent observations and analyses of absorption in quasar spectra suggest a rapid drop in the mean free path (MFP) at the late stage of reionization at z ∼ 6 . We use the Cosmic Reionization on Computers simulation to examine potential biases in observed measurements of the MFP at the late stage of reionization, particularly in the presence of a quasar. We analyze three snapshots surrounding the ‘ankle’ point of reionization history, when extended neutral patches of the intergalactic medium disappeared in the simulation box. Specifically, these are z = 6.8 (true MFP ≈ 0.4 ~pMpc), in addition to z = 6.1 (true MFP ≈ 2 ~pMpc) and z = 5.4 (true MFP ≈ 6 ~pMpc). We compare the inferred MFP from synthetic spectra fits to the true MFP. We find that the mean Lyman continuum (LyC) profile at z = 6.8 changes significantly with quasar lifetime t Q . We attribute this sensitivity to t Q to a combination of extended neutral IGM patches and the prevalence of small-scale dense clumps. Consequently, the inferred MFP can be biased by a factor of few depending on t Q . On the other hand, for the z = 6.1 and z = 5.4 snapshots, the mean LyC profile shows minimal sensitivity to variation in t Q ≳ 1 Myr. The inferred MFP in these two cases is accurate to the ≲ 30 % level. Our results highlight how modeling systematics can affect the inferred MFP, particularly in the regime of small true MFP ( ≲ 0.5 pMpc). We also discuss the potential of this regime to provide a testing ground for constraining quasar lifetimes from LyC profiles.
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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 | 0.002 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".