Dust and star formation properties of a complete sample of local galaxies drawn from the Planck Early Release Compact Source Catalogue
Bibliographic record
Abstract
We combine Planck High Frequency Instrument data at 857, 545, 353 and 217 GHz with data from Wide-field Infrared Survey Explorer (WISE), Spitzer, IRAS and Herschel to investigate the properties of a well-defined, flux-limited sample of local star-forming galaxies. A 545 GHz flux density limit was chosen so that the sample is 80 per cent complete at this frequency, and the resulting sample contains a total of 234 local, star-forming galaxies. We investigate the dust emission and star formation properties of the sample via various models and calculate the local dust mass function. Although single-component-modified blackbodies fit the dust emission longward of 80 μm very well, with a median β = 1.83, the known degeneracy between dust temperature and β also means that the spectral energy distributions are very well described by a dust component with dust emissivity index fixed at β = 2 and temperature in the range 10–25 K. Although a second, warmer dust component is required to fit shorter wavelength data, and contributes approximately a third of the total infrared emission, its mass is negligible. No evidence is found for a very cold (6–10 K) dust component. The temperature of the cold dust component is strongly influenced by the ratio of the star formation rate to the total dust mass. This implies, contrary to what is often assumed, that a significant fraction of even the emission from ∼20 K dust is powered by ongoing star formation, whether or not the dust itself is associated with star-forming clouds or ‘cirrus’. There is statistical evidence of a free–free contribution to the 217 GHz flux densities of ≲20 per cent. We find a median dust-to-stellar mass ratio of 0.0046; and that this ratio is anticorrelated with galaxy mass. There is good correlation between dust mass and atomic gas mass (median Md/MHI = 0.022), suggesting that galaxies that have more dust (higher values of Md/M*) have more interstellar medium in general. Our derived dust mass function implies a mean dust mass density of the local Universe (for dust within galaxies), of 7.0 ± 1.4 × 105 M⊙ Mpc−3, significantly greater than that found in the most recent estimate using Herschel data.
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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 | 0.001 | 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) | 0.003 | 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".