Probing Structure in Cold Gas at z ≲ 1 with Gravitationally Lensed Quasar Sight Lines
Bibliographic record
Abstract
Abstract Absorption spectroscopy of gravitationally lensed quasars (GLQs) enables study of spatial variations in the interstellar and/or circumgalactic medium of foreground galaxies. We report observations of four GLQs, each with two images separated by 0.″8–3.″0, that show strong absorbers at redshifts 0.4 < z abs < 1.3 in their spectra, including some at the lens redshift with impact parameters 1.5–6.9 kpc. We measure H i Lyman lines along two sight lines each in five absorbers (10 sight lines in total) using Hubble Space Telescope Space Telescope Imaging Spectrograph, and metal lines using Magellan Echellette or Sloan Digital Sky Survey. Our data have doubled the lens galaxy sample with measurements of H i column densities (N H i ) and metal abundances along multiple sight lines. Our data, combined with the literature, show no strong correlation between absolute values of differences in N H i , N Fe ii , or [Fe/H] and the sight line separations at the absorber redshifts for separations of 0–8 kpc. The estimated abundance gradients show a tentative anticorrelation with abundances at galaxy centers. Some lens galaxies show inverted gradients, possibly suggesting central dilution by mergers or infall of metal-poor gas. [Fe/H] measurements and masses estimated from GLQ astrometry suggest the lens galaxies lie below the total mass–metallicity relation for early-type galaxies as well as measurements for quasar-galaxy pairs and gravitationally lensed galaxies at comparable redshifts. This difference may arise in part from the dust depletion of Fe. Higher resolution measurements of H and metals (especially undepleted elements) for more GLQ absorbers and accurate lens redshifts are needed to confirm these trends.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".