Infrared luminosity functions of AKARI Sloan Digital Sky Survey galaxies
Bibliographic record
Abstract
By cross-correlating the AKARI all-sky survey in six infrared (IR) bands (9, 18, 65, 90, 140 and 160 μm) with the Sloan Digital Sky Survey (SDSS) galaxies, we identified 2357 IR galaxies with a spectroscopic redshift. This is not just one of the largest samples of local IR galaxies, but AKARI provides crucial far-IR (FIR) bands for accurately measuring the galaxy spectral energy distribution (SED) across the peak of the dust emission at > 100 μ m. By fitting modern IR SED models to the AKARI photometry, we measured the total infrared luminosity (LIR) of individual galaxies. Using this LIR, we constructed the luminosity functions (LF) of IR galaxies at a median redshift of z= 0.031. The LF agrees well with that at z= 0.0082 (the Revised Bright Galaxy Sample), showing smooth and continuous evolution towards higher redshift LFs measured in the AKARI North Ecliptic Pole (NEP) deep field. By integrating the IR LF weighted by LIR, we measured the local cosmic IR luminosity density of ΩIR= (3.8+5.8−1.2) × 108 L⊙ Mpc−3. We separate galaxies into active galactic nuclei (AGN), star-forming galaxies (SFG) and composite by using the [N ii]/Hα versus [O iii]/Hβ line ratios. The fraction of AGN shows a continuous increase with increasing LIR from 25 to 90 per cent at 9 < log LIR < 12.5. The SFRHα and show good correlations with LIR for SFG and AGN, respectively. The self-absorption-corrected Hα/Hβ ratio shows a weak increase with LIR with a substantial scatter. When we separate IR LFs into contributions from AGN and SFG, the AGN contribution becomes dominant at LIR > 1011 L⊙, coinciding with the break of both the SFG and AGN IR LFs. At LIR≤ 1011 L⊙, SFG dominates IR LFs. Only 1.1 ± 0.1 per cent of ΩIR is produced by luminous infrared galaxies (LIR > 1011 L⊙), and only 0.03 ± 0.01 per cent by ultraluminous infrared galaxies (LIR > 1012 L⊙) in the local Universe. Compared with high-redshift results from the AKARI NEP deep survey, we observed a strong evolution of ΩSFGIR∝ (1 +z)4.1±0.4 and ΩAGNIR∝ (1 +z)4.1±0.5. Our results show that all of our measured quantities (IR LFs, L*, ΩAGNIR, ΩSFGIR) show smooth and steady increase from lower redshift (the Revised Bright Galaxy Sample) to higher redshift (the AKARI NEP deep survey).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".