The Interstellar Medium in High-redshift Submillimeter Galaxies as Probed by Infrared Spectroscopy<sup>∗</sup>
Bibliographic record
Abstract
Abstract Submillimeter galaxies (SMGs) at are luminous in the far-infrared, and have star formation rates, SFR, of hundreds to thousands of solar masses per year. However, it is unclear whether they are true analogs of local ULIRGs or whether the mode of their star formation is more similar to that in local disk galaxies. We target these questions by using Herschel-PACS to examine the conditions in the interstellar medium (ISM) in far-infrared luminous SMGs at –4. We present 70–160 μm photometry and spectroscopy of the [O iv]26 μm, [Fe ii]26 μm, [S iii]33 μm, [Si ii]34 μm, [O iii]52 μm, [N iii]57 μm, and [O i]63 μm fine-structure lines and the S(0) and S(1) hydrogen rotational lines in 13 lensed SMGs identified by their brightness in early Herschel data. Most of the 13 targets are not individually spectroscopically detected; we instead focus on stacking these spectra with observations of an additional 32 SMGs from the Herschel archive—representing a complete compilation of PACS spectroscopy of SMGs. We detect [O i]63 μm, [Si ii]34 μm, and [N iii]57 μm at in the stacked spectra, determining that the average strengths of these lines relative to the far-IR continuum are , , and , respectively. Using the [O iii]52 μm/[N iii]57 μm emission line ratio, we show that SMGs have average gas-phase metallicities . By using PDR modeling and combining the new spectral measurements with integrated far-infrared fluxes and existing [C ii]158 μm data, we show that SMGs have average gas densities, n, of and FUV field strengths, (in Habing units: ), consistent with both local ULIRGs and lower luminosity star-forming galaxies.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".