Metal enrichment and evolution in four <i>z</i> > 6.5 quasar sightlines observed with JWST/NIRSpec
Bibliographic record
Abstract
We present JWST/NIRSpec R ≃ 2700 spectra of four high-redshift quasars: VDES J0020–3653 (z = 6.860), DELS J0411–0907 (z = 6.825), UHS J0439+1634 (z = 6.519), and ULAS J1342+0928 (z = 7.535). The exquisite data quality, signal-to-noise ratio of 50–200, and large 0.86 μm ≤ λ ≤ 5.5 μm spectral coverage allowed us to identify between 13 and 17 intervening and proximate metal absorption line systems in each quasar spectrum, with a total number of 61 absorption-line systems detected at 2.42 < z < 7.48 including the highest redshift intervening O Iλ1302 and Mg II systems at z = 7.37 and z = 7.44. We investigated the evolution of the metal enrichment in the epoch of re-ionisation (EoR) at z > 6 and found the following: i) a continued increase in the low-ionisation O I, C II, and Si II incidence, ii) decreasing high-ionisation C IV and Si IV incidence with a transition from predominantly high- to low-ionisation at z ≈ 6.0, and iii) a constant Mg II incidence across all redshifts. The observations support a change in the ionisation state of the intergalactic medium in the EoR rather than a change in metallicity. The abundance ratio of [Si/O] in five z > 6 absorption systems show enrichment signatures produced by low-mass Pop III pair instability supernovae, and possibly Pop III hypernovae. In the Gunn-Peterson troughs, we detected transmission spikes where Lyα photons can escape. From 22 intervening absorption line systems at z > 5.7, only a single low-ionisation system out of 13 lies within 2000 km s−1 from a spike, while four high-ionisation systems out of nine lie within ∼2000 km s−1 from a spike. Most spikes do not have associated metal absorbers close by. This confirms that star-forming galaxies responsible for producing the heavy elements that are transported to the circumgalactic medium via galaxy winds do so in predominantly high-density, neutral environments, while lower density environments are ionised without being polluted by metals at z ≈ 6 − 7.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".