Fast Outflows in Hot Dust-obscured Galaxies Detected with Keck/NIRES
Bibliographic record
Abstract
Abstract We present rest-frame optical spectroscopic observations of 24 Hot Dust-Obscured Galaxies (Hot DOGs) at redshifts 1.7–4.6 with KECK/NIRES. Our targets are selected, based on their extreme red colors, to be the highest-luminosity sources from the WISE infrared survey. In 20 sources with well-detected emission, we fit the key [O iii ], H β , H α , [N ii ], and [S ii ] diagnostic lines to constrain physical conditions. Of the 17 targets with a clear detection of the [O iii ] λ 5007 Å emission line, 15 display broad blueshifted and asymmetric line profiles, with widths ranging from 1000 to 8000 km s −1 and blueshifts up to 3000 km s −1 . These kinematics provide strong evidence for the presence of massive ionized outflows of up to , with a median of . As many as eight sources show optical emission line ratios consistent with vigorous star formation. Balmer-line star formation rates, uncorrected for reddening, range from 30 to 1300 , with a median of . Estimates of the SFR from Spectral Energy Distribution fitting of mid- and far-infrared photometry suggest significantly higher values. We estimate the central black hole masses to be of order , assuming the present-day relation. The bolometric luminosities and the estimated masses of the central black holes of these galaxies suggest that many of the active galactic nucleus-dominated Hot DOGs are accreting at or above their Eddington limit. The combination of ongoing star formation, massive outflows, and high Eddington ratios suggest Hot DOGs are a transitional phase in galaxy evolution.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".