FAR-IR/SUBMILLIMETER SPECTROSCOPIC COSMOLOGICAL SURVEYS: PREDICTIONS OF INFRARED LINE LUMINOSITY FUNCTIONS FOR z < 4 GALAXIES
Bibliographic record
Abstract
ABSTRACT Star formation and accretion onto supermassive black holes in the nuclei of galaxies are the two most energetic processes in the universe, producing the bulk of the observed emission throughout its history. We simulated the luminosity functions of star-forming and active galaxies for spectral lines that are thought to be good spectroscopic tracers of either phenomenon, as a function of redshift. We focused on the infrared (IR) and submillimeter domains, where the effects of dust obscuration are minimal. Using three different and independent theoretical models for galaxy formation and evolution, constrained by multi-wavelength luminosity functions, we computed the number of star-forming and active galaxies per IR luminosity and redshift bin. We converted the continuum luminosity counts into spectral line counts using relationships that we calibrated on mid- and far-IR spectroscopic surveys of galaxies in the local universe. Our results demonstrate that future facilities optimized for survey-mode observations, i.e., the Space Infrared telescope for Cosmology and Astrophysics and the Cerro Chajnantor Atacama Telescope, will be able to observe thousands of z > 1 galaxies in key fine-structure lines, e.g., [Si ii], [O i], [O iii], [C ii], in a half-square-degree survey, with 1 hr integration time per field of view. Fainter lines such as [O iv], [Ne v], and H2 (0–0)S1 will be observed in several tens of bright galaxies at 1 < z < 2, while diagnostic diagrams of active nucleus versus star formation activity will be feasible even for normal z ∼ 1 galaxies. We discuss the new parameter space that these future telescopes will cover and that strongly motivates their construction.
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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 | 0.002 | 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 | 0.000 |
| Research integrity | 0.001 | 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".