Clues to the nature of high-redshift O vi absorption systems from their lack of small-scale structure
Bibliographic record
Abstract
We present results of the first survey of high-redshift absorption systems along parallel lines of sight toward two lensed QSOs. After a careful and well-defined search, we find ten intervening systems – identified by the presence of the 1031, 1037 doublet lines, , and in most cases , , and – and eight candidate systems for which we do not detect nor other metals. We assess the veracity of these systems by applying a classification scheme. Within the errors, all systems appear at the same redshift and have similar line strengths in front of both QSO images, whereas in most cases or show more differences across the lines of sight, either in radial velocity or line strength. We conclude that (1) the coherence length of must be much larger than 1 kpc, and (2) an important fraction of the absorbers may not reside in the same volume as . Given the inhomogeneous character of the data – different ratios and degrees of blending – we pay special attention to the observational errors and their impact on the above conclusions. Since Doppler parameters are consistent with photoionization, we propose a model in which occurs in two different photoionized phases, one large, with characteristic sizes of a few hundred kpc and bearing , and another one a factor of ten smaller and containing . This model is able to explain the various transverse differences observed in column density and kinematics. We apply the model successfully to 2 kinds of absorbers, with low and high metallicity. In the low-metallicity regime, [C/H]~ -2, we find that [C/O] ≈ -0.7 is required to explain the observations, which hints at late () rather than early metal enrichment. In the high-metallicity regime, the observed dissociation between and gas might be produced by galactic outflows. Altogether, the relative abundances, inhomogeneous and featureless are consistent with gas that has been processed recently before the absorption occurred (thus close to star-forming regions). Finally, we discuss briefly three associated systems that also show .
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".