Strong Mg ii and Fe ii Absorbers at 2.2 < z < 6.0
Bibliographic record
Abstract
Abstract We present a study of strong intervening absorption systems in the near-IR spectra of 31 luminous quasars at z > 5.7. The quasar spectra were obtained with Gemini GNIRS that provide continuous wavelength coverage from ∼0.9 to ∼2.5 μm. We detect 32 strong Mg ii doublet absorbers with rest-frame equivalent width W r (λ2796) > 1.0 Å at 2.2 < z < 6.0. Each Mg ii absorber is confirmed by at least two associated Fe ii absorption lines in the rest-frame wavelength range of ∼1600–2600 Å. We find that the comoving line density (dN/dX) of the strong Fe ii-bearing Mg ii absorbers decreases toward higher redshift at z > 3, consistent with previous studies. Compared with strong Mg ii absorbers detected in damped Lyα systems at 2 < z < 4, our absorbers are potentially less saturated and show much larger rest-frame velocity widths. This suggests that the gas traced by our absorbers are potentially affected by galactic superwinds. We analyze the Hubble Space Telescope near-IR images of the quasars and identify possible associated galaxies for our strong absorbers. There are a maximum of two galaxy candidates found within 5″ radius of each absorber. The median F105W-band magnitude of these galaxy candidates is 24.8 mag, which is fainter than the L* galaxy luminosity at z ∼ 4. By using our observed dN/dX of strong Mg ii absorbers and galaxy candidates median luminosity, we suggest that at high redshift, strong Mg ii absorbers tend to have a more disturbed environment but smaller halo size than that at z < 1.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".