Evolution of the population of very strong Mg II absorbers
Bibliographic record
Abstract
Abstract We present a study of the evolution of several classes of Mg ii absorbers, and their corresponding Fe ii absorption, over a large fraction of cosmic history: 2.3–8.7 Gyr from the big bang. Our sample consists of 87 strong ( Å) Mg ii absorbers, with redshifts 0.2 < z < 2.5, measured in 81 quasar spectra obtained from the Very Large Telescope/Ultraviolet and Visual Echelle Spectrograph archives of high-resolution spectra (R ∼ 45 000). No evolutionary trend in is found for moderately strong Mg ii absorbers ( Å). However, at lower redshifts we find an absence of very strong Mg ii absorbers (those with Å) with small ratios of equivalent widths of Fe ii to Mg ii. At high redshifts, very strong Mg ii absorbers with both small and large values are present. We compare our findings to a sample of 100 weak Mg ii absorbers ( Å) found in the same quasar spectra by Narayanan et al. The main effect driving the evolution of very strong Mg ii systems is the difference between the kinematic profiles at low and high redshift. At high redshift, we observe that, among the very strong Mg ii absorbers, all of the systems with small ratios of Wr(Fe II)/Wr(Mg II) have relatively large velocity spreads, resulting in less saturated profiles. At low redshift, such kinematically spread systems are absent, and both Fe ii and Mg ii are saturated, leading to Wr(Fe II)/Wr(Mg II) values that are all close to 1. The high redshift, small Wr(Fe II)/Wr(Mg II) systems could correspond to sub-damped Lyman α systems, many of which have large velocity spreads and are possibly linked to superwinds in star-forming galaxies. In addition to the change in saturation due to kinematic evolution, the smaller Wr(Fe II)/Wr(Mg II) values could be due to a lower abundance of Fe at high redshifts, which would indicate relatively early stages of star formation in those environments.
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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 | 0.002 | 0.001 |
| 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".