A BACKWARD EVOLUTION MODEL FOR INFRARED SURVEYS: THE ROLE OF AGN– AND COLOR–<i>L</i><sub>TIR</sub>DISTRIBUTIONS
Bibliographic record
Abstract
Empirical "backward" galaxy evolution models for infrared (IR) bright galaxies are constrained using multiband IR surveys. We developed a new Monte Carlo algorithm for this task, implementing luminosity-dependent distribution functions for the galaxies' IR spectral energy distributions (SEDs) and for the active galactic nucleus (AGN) contribution, allowing for evolution of these quantities. The adopted SEDs take into account the contributions of both starbursts and AGN to the IR emission, for the first time in a coherent treatment rather than invoking separate AGN and star-forming populations. In the first part of the paper we consider the quantification of the AGN contribution for local universe galaxies, as a function of the total IR luminosity. It is made using a large sample of luminous infrared galaxies and ultraluminous infrared galaxies for which mid-IR spectra are available in the Spitzer archive. We find the ratio of AGN 6 μm luminosity and the total IR luminosity to rise with L 1.4 TIR over the IR luminosity range 10 11 –10 13 L ☉ and estimate its spread. Judging from the modest number of distant sources with Spitzer spectroscopy, the relation changes at high- z . In the second part we present the model. Our best-fit model adopts very strong luminosity evolution, L = L 0 (1 + z ) 3.4 , up to z = 2.3, and density evolution, ρ = ρ 0 (1 + z ) 2 , up to z = 1, for the population of IR galaxies. At higher z , the evolution rates drop as (1 + z ) −1 and (1 + z ) −1.5 , respectively. To reproduce mid-IR to submillimeter number counts and redshift distributions, it is necessary to introduce both an evolution in the AGN contribution and an evolution in the luminosity–temperature relation. At a given total IR luminosity, high-redshift IR galaxies have typically smaller AGN contributions to the rest-frame mid-IR, and colder far-IR dust temperatures than locally. We also suggest an extension of the local IR galaxy population toward lower dust temperatures. Our models are in plausible agreement with current photometry-based estimates of the typical AGN contribution as a function of mid-IR flux, and well placed to be compared to upcoming Spitzer spectroscopic results. As an example of future applications, we use our best-fitting model to make predictions for surveys with Herschel .
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".