Probing star formation across cosmic time with absorption-line systems
Bibliographic record
Abstract
We present an empirical connection between cold (∼104 K) gas in galactic haloes and star formation. Using a sample of more than 8500 Mg ii absorbers from Sloan Digital Sky Survey (SDSS) quasar spectra, we report the detection of a 15σ correlation between the rest equivalent width W0 of Mg ii absorbers and the associated [O ii] luminosity, an estimator of star formation rate. This correlation has interesting implications: using only observable quantities we show that Mg ii absorbers trace a substantial fraction of the global [O ii] luminosity density and recover the overall star formation history of the Universe derived from classical emission estimators up to z∼ 2. We then show that the distribution function of Mg ii rest equivalent widths, dN/dW0, inherits both its shape and amplitude from the [O ii] luminosity function Φ(L). These distributions can be naturally connected, without any free parameter. Our results imply a high covering factor of cold gas around star-forming galaxies: C≳ 0.5, favouring outflows as the mechanism responsible for Mg ii absorption. We then argue that intervening Mg ii absorbers and blueshifted Mg ii absorption seen in the spectra of star-forming galaxies are essentially the same systems, implying that the observed outflowing gas can reach radii of ∼50 kpc. These results not only shed light on the nature of Mg ii absorbers but also provide us with a new probe of star formation, in absorption, i.e. in a way which does not suffer from dust extinction and with a redshift-independent sensitivity. As shown in this analysis, such a tool can be applied in a noise-dominated regime, i.e. using a data set for which emission lines are not detected in individual objects. This is of particular interest for high-redshift studies.
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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 | 0.002 |
| 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".