ISM Properties in Low-Metallicity Environments III. The Dust Spectral Energy Distributions of II Zw 40, He 2-10 and NGC 1140
Bibliographic record
Abstract
We present new 450 and 850 micron SCUBA data and 1.3 mm MAMBO data of the dwarf galaxies II Zw 40, He 2-10 and NGC 1140. Additional ISOCAM, IRAS as well as ground based data are used to construct the observed mid-infrared to millimeter spectral energy distribution of these galaxies. These spectral energy distributions are modeled in a self-consistent way, as was achieved with NGC 1569 (Galliano et al., 2003), synthesizing both the global stellar radiation field and the dust emission, with further constraints provided by the photoionisation of the gas. Our study shows that low-metallicity galaxies have very different dust properties compared to the Galaxy. Our main results are: (i) a paucity of PAHs which are likely destroyed by the hard penetrating radiation field, (ii) a very small (3-4 nm) average size of grains, consistent with the fragmentation and erosion of dust particles by the numerous shocks, (iii) a significant millimetre excess in the dust spectral energy distribution which can be explained by the presence of ubiquitous very cold dust (T=5-9 K) accounting for 40 to 80 % of the total dust mass, probably distributed in small clumps. We derive a range of gas-to-dust mass ratios between 300 and 2000, larger than the Galactic values and dust-to-metals ratios of 1/30 to 1/2. The modeled dust size distributions are used to synthesize an extinction curve for each galaxy. The UV slopes of the extinction curves resemble that observed in some regions in the Large Magellanic Cloud. The 2175 angstrom bumps of the modeled extinction curves are weaker than that of the Galaxy, except in the case of II Zw 40, where we are unable to accurately constrain the 2175 angstrom bump carrier.
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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 | 0.000 |
| 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 | 0.001 | 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".