Extended H<i>α</i> over compact far-infrared continuum in dusty submillimeter galaxies
Bibliographic record
Abstract
By using data from the Atacama Large Millimeter/submillimeter Array and near-infrared (NIR) integral field spectrographs, including both Spectrograph for INtegral Field Observations in the Near Infrared and K-band Multi Object Spectrograph on the Very Large Telescope, we investigate the two-dimensional distributions of Hα and rest-frame far-infrared (FIR) continuum in six submillimeter galaxies (SMGs) at z ∼ 2. At a similar spatial resolution (∼0.″5 FWHM; ∼4.5 kpc at z = 2), we find that the half-light radius of Hα is significantly larger than that of the FIR continuum in half of the sample, and on average Hα is a median factor of 2.0 ± 0.4 larger. Having explored various ways to correct for the attenuation, we find that the attenuation-corrected Hα-based star-formation rates (SFRs) are systematically lower than the infrared (IR)-based SFRs by at least a median factor of 3 ± 1, which cannot be explained by the difference in half-light radius alone. In addition, we find that in 40% of cases the total V-band attenuation (AV) derived from energy balance modeling of the full ultraviolet (UV)-to-FIR spectral energy distributions (SEDs) is significantly higher than what is derived from SED modeling using only the UV-to-NIR part of the SEDs, and the discrepancy appears to increase with increasing total infrared luminosity. Finally, in considering all of our findings along with the studies in the literature, we postulate that the dust distributions in SMGs, and possibly also in less IR luminous z ∼ 2 massive star-forming galaxies, can be decomposed into the following three main components: the diffuse dust heated by older stellar populations, the more obscured and extended young star-forming H II regions, and the heavily obscured central regions that have a low filling factor but dominate the infrared luminosity in which the majority of attenuation cannot be probed via UV-to-NIR emissions.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".