A Spatially Resolved Study of Cold Dust, Molecular Gas, H ii Regions, and Stars in the z = 2.12 Submillimeter Galaxy ALESS67.1
Bibliographic record
Abstract
Abstract We present detailed studies of a z = 2.12 submillimeter galaxy, ALESS67.1, using sub-arcsecond resolution ALMA, adaptive optics-aided VLT/SINFONI, and Hubble Space Telescope (HST)/CANDELS data to investigate the kinematics and spatial distributions of dust emission (870 μm continuum), 12CO(J = 3–2), strong optical emission lines, and visible stars. Dynamical modeling of the optical emission lines suggests that ALESS67.1 is not a pure rotating disk but a merger, consistent with the apparent tidal features revealed in the HST imaging. Our sub-arcsecond resolution data set allows us to measure half-light radii for all the tracers, and we find a factor of 4–6 smaller sizes in dust continuum compared to all the other tracers, including 12CO; also, ultraviolet (UV) and Hα emission are significantly offset from the dust continuum. The spatial mismatch between the UV continuum and the cold dust and gas reservoir supports the explanation that geometrical effects are responsible for the offset of the dusty galaxy on the IRX–β diagram. Using a dynamical method we derive an , consistent with other submillimeter galaxies (SMGs) that also have resolved CO and dust measurements. Assuming a single value we also derive resolved gas and star formation rate surface densities, and find that the core region of the galaxy ( kpc) follows the trend of mergers on the Schmidt–Kennicutt relationship, whereas the outskirts ( kpc) lie on the locus of normal star-forming galaxies, suggesting different star formation efficiencies within one galaxy. Our results caution against using single size or morphology for different tracers of the star formation activity and gas content of galaxies, and therefore argue the need to use spatially resolved, multi-wavelength observations to interpret the properties of SMGs, and perhaps even for galaxies in general.
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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 | 0.000 |
| 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) | 0.000 | 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".