Investigating Mg <scp>ii</scp>absorption in paired quasar sight-lines
Bibliographic record
Abstract
We test whether the Tinker & Chen model of MgII absorption due to the gaseous halo around a galaxy can reproduce absorption in quasar pairs (both lensed and physical) and lensed triples and quads from the literature. These quasars exhibit absorption from a total of 38 MgII systems spanning z=0.043 - 2.066 with mean redshift =1.099 and weighted mean rest-frame equivalent width of 0.87 Ang. Using the Tinker & Chen model to generate simulated sight-lines, we marginalize the unknown parameters of the absorbing galaxies: dark matter halo mass, impact parameter, and azimuthal angle on the sky. We determine the ability of the model to statistically reproduce the observed variation in MgII absorption strength between paired sight-lines for different values of the gas covering fraction f_c and the characteristic length scale ell_c, within which the variation in absorption equivalent widths between sight-lines exponentially decreases. We find a best-fit f_c=0.60 \pm 0.15 and ell_c<8/h_70 kpc (1σconfidence limits), with smaller f_c allowed at larger ell_c. At 99.7% confidence, we are able to rule out f_c>0.87 for all values of ell_c and the region where ell_c<1.0/h_70 kpc and f_c<0.3.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".