The Galaxies Missed by Hubble and ALMA: The Contribution of Extremely Red Galaxies to the Cosmic Census at 3 < z < 8
Bibliographic record
Abstract
Abstract Using deep JWST imaging from JADES, JEMS, and SMILES, we characterize optically faint and extremely red galaxies at z > 3 that were previously missing from galaxy census estimates. The data indicate the existence of abundant, dusty, and poststarburst-like galaxies down to 10 8 M ⊙ , below the sensitivity limit of Spitzer and the Atacama Large Millimeter/submillimeter Array (ALMA). Modeling the NIRCam and Hubble Space Telescope (HST) photometry of these red sources can result in extremely high values for both stellar mass and star formation rate (SFR); however, including seven MIRI filters out to 21 μ m results in decreased masses (median 0.6 dex for log 10 ( M ∗ / M ⊙ ) > 10) and SFRs (median 10× for SFR > 100 M ⊙ yr −1 ). At z > 6, our sample includes a high fraction of "little red dots" (LRDs; NIRCam-selected dust-reddened active galactic nucleus (AGN) candidates). We significantly measure older stellar populations in the LRDs out to rest-frame 3 μ m (the stellar bump) and rule out a dominant contribution from hot dust emission, a signature of AGN contamination to stellar population measurements. This allows us to measure their contribution to the cosmic census at z > 3, below the typical detection limits of ALMA ( L IR < 10 12 L ⊙ ). We find that these sources, which are overwhelmingly missed by HST and ALMA, could effectively double the obscured fraction of the star formation rate density at 4 < z < 6 compared to some estimates, showing that prior to JWST, the obscured contribution from fainter sources could be underestimated. Finally, we identify five sources with evidence for Balmer breaks and high stellar masses at 5.5 < z < 7.7. While spectroscopy is required to determine their nature, we discuss possible measurement systematics to explore with future data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".