Metal Lines Associated with the Lyα Forest from eBOSS Data
Bibliographic record
Abstract
Abstract We investigate the metal species associated with the Lyα forest in eBOSS quasar spectra. Metal absorption lines are revealed in stacked spectra from cross-correlating the selected Lyα absorbers in the forest and the flux fluctuation field. Up to 13 metal species are identified as being associated with relatively strong Lyα absorbers (those with flux fluctuations − 1.0 < δ Lyα < − 0.6 and with a neutral hydrogen column density of ∼ 1015−16 cm−2) over the absorber redshift range of 2 < z abs < 4. The column densities of these species decrease toward higher redshift and for weaker Lyα absorbers. From modeling the column densities of various species, we find that the column density pattern suggests contributions from multiple gas components, both in the circumgalactic medium (CGM) and the intergalactic medium (IGM). While the low-ionization species (e.g., C ii, Si ii, and Mg ii) can be explained by high-density, cool gas (T ∼ 104 K) from the CGM, the high-ionization species may reside in low-density or high-temperature gas in the IGM. The measurements provide inputs for modeling the metal contamination in the Lyα forest baryon acoustic oscillation measurements. Comparisons with metal absorptions in high-resolution quasar spectra and hydrodynamic galaxy formation simulations can further elucidate the physical conditions of these Lyα absorbers.
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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".