The Resolved Behavior of Dust Mass, Polycyclic Aromatic Hydrocarbon Fraction, and Radiation Field in ∼800 Nearby Galaxies
Bibliographic record
Abstract
Abstract We present resolved 3.6–250 μ m dust spectral energy distribution (SED) fitting for ∼800 nearby galaxies. We measure the distribution of radiation field intensities heating the dust, the dust mass surface density (Σ d ), and the fraction of dust in the form of polycyclic aromatic hydrocarbons (PAHs; q PAH ). We find that the average interstellar radiation field ( U ¯ ) is correlated both with stellar mass surface density (Σ ⋆ ) and star formation rate surface density (Σ SFR ), while more intense radiation fields are only correlated with Σ SFR . We show that q PAH is a steeply decreasing function of Σ SFR , likely reflecting PAH destruction in H ii regions. Galaxy-integrated q PAH is strongly, negatively correlated with specific star formation rate (sSFR) and offset from the star-forming “main sequence” (ΔMS), suggesting that both metallicity and star formation intensity play a role in setting the global q PAH . We also find a nearly constant M d / M * ratio for galaxies on the main sequence, with a lower ratio for more quiescent galaxies, likely due to their lower gas fractions. From these results, we construct prescriptions to estimate the radiation field distribution in both integrated and resolved galaxies. We test these prescriptions by comparing our predicted U ¯ to results of SED fitting for stacked “main-sequence” galaxies at 0 < z < 4 from M. Béthermin et al. and find sSFR is an accurate predictor of U ¯ even at these high redshifts. Finally, we describe the public delivery of matched-resolution Wide-field Infrared Survey Explorer and Herschel maps along with the resolved dust SED-fitting results through the Infrared Science Archive.
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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 | 0.000 |
| 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".