JWST’s PEARLS: Resolved study of the stellar and dust components in starburst galaxies at cosmic noon
Bibliographic record
Abstract
Dusty star-forming galaxies (DSFGs) significantly contribute to the stellar buildup in galaxies during “cosmic noon,” the peak epoch of cosmic star formation. Major mergers and gas accretion are often invoked to explain DSFGs’ prodigious star formation rates (SFRs) and large stellar masses. We conducted a spatially resolved morphological analysis of the rest-frame ultraviolet/near-infrared (∼0.25–1.3 μm) emission in three DSFGs at z ≃ 2.5. Initially discovered as carbon monoxide (CO) emitters by NOrthern Extended Millimeter Array (NOEMA) observations of a bright (S350 μm = 111 ± 10 mJy) Herschel source, we observed them with the James Webb Space Telescope/NIRCam as part of the PEARLS program. The NIRCam data reveal the galaxies’ stellar populations and dust distributions on scales of 250 pc. Spatial variations in stellar mass, SFR, and dust extinction are determined in resolved maps obtained through pixel-based spectral energy distribution fitting. The CO emitters are massive (Mstar ≃ (3 − 30)×1010 M⊙), dusty starburst galaxies with SFRs ranging from 340 to 2500 M⊙ yr−1, positioning them among the most active star-forming galaxies at 2 < z < 3. Notably, they belong to the ∼1.5% of the entire JWST population with extremely red colors. Their morphologies are disk like (Sérsic index n ≃ 1), with effective radii of 2.0–4.4 kpc, and exhibit substructures such as clumps and spiral arms. The galaxies have dust extinctions up to AV = 5–7 mag extending over several kiloparsecs with asymmetric distributions that include off-center regions resembling bent spiral arms and clumps. The near-infrared dust-attenuation curve in these sources deviates from standard laws, possibly implying different dust–star geometries or dust grain properties than commonly assumed in starburst galaxies. The proximity (< 5″) of galaxies with consistent redshifts, strong color gradients, an overall disturbed appearance, asymmetric dust obscuration, and widespread star formation collectively favor interactions (minor mergers and flybys) as the mechanism driving the CO galaxies’ exceptional SFRs. The galaxies’ large masses and rich environment hint at membership in two proto-structures, as initially inferred from their association with a Planck-selected high-z source.
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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 | 0.001 |
| 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) | 0.001 | 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".