Mid‐Infrared Spectral Diagnosis of Submillimeter Galaxies
Bibliographic record
Abstract
We present deep mid-IR spectroscopy with Spitzer of 13 SMGs in the GOODS-N field. We find strong PAH emission in all of our targets, which allows us to measure mid-IR spectroscopic redshifts and place constraints on the contribution from star formation and AGN activity to the mid-IR emission. In the high-S/N composite spectrum, we find that the hot dust continuum from an AGN contributes at most 30% of the mid-IR luminosity. Individually, only 2/13 SMGs have continuum emission dominating the mid-IR luminosity; one of these SMGs, C1, remains undetected in the deep X-ray images but shows a steeply rising continuum in the mid-IR indicative of a Compton-thick AGN. We find that the mid-IR properties of SMGs are distinct from those of 24 μm-selected ULIRGs at z ∼ 2; the former are predominantly dominated by star formation, while the latter are a more heterogeneous sample with many showing significant AGN activity. We fit the IRS spectrum and the mid-IR to radio photometry of SMGs with template SEDs to determine the best estimate of the total IR luminosity from star formation. While many SMGs contain an AGN as evinced by their X-ray properties, our multiwavelength analysis shows that the total IR luminosity, L IR , in SMGs is dominated by star formation. We find that high-redshift SMGs lie on the relation between L IR and L PAH ,6.2 (or L PAH ,7.7 or L PAH ,11.3 ) that has been established for local starburst galaxies. This suggests that PAH luminosity can be used as a proxy for the SFR in SMGs. SMGs are consistent with being a short-lived cool phase in a massive merger where the AGN does not appear to have become strong enough to heat the dust and dominate the mid- or far-IR emission.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".