The ALPINE-ALMA [CII] survey: Dust emission effective radius up to 3 kpc in the early Universe
Bibliographic record
Abstract
Aims. Measurements of the size of dust continuum emission are an important tool for constraining the spatial extent of star formation, and hence the buildup of stellar mass. Compact dust emission has generally been observed at cosmic noon (z ∼ 2 − 3). However, at earlier epochs, toward the end of the reionization (z ∼ 4 − 6), only the sizes of a handful of infrared (IR) bright galaxies have been measured. In this work, we derive the dust emission sizes of main-sequence (MS) galaxies at z ∼ 5 from the ALPINE survey. Methods. We measured the dust effective radius, re, FIR, in the uv-plane in Band 7 of ALMA for seven ALPINE galaxies with resolved emission and we compared it with rest-frame ultraviolet (UV) and [CII]158 μm measurements. We studied the re, FIR − LIR scaling relation by considering our dust size measurements and all the data in the literature at z ∼ 4 − 6. Finally, we compared our size measurements with predictions from simulations. Results. The dust emission in the selected ALPINE galaxies is rather extended (re, FIR ∼ 1.5 − 3 kpc), similar to [CII]158 μm but a factor of ∼2 larger than the rest-frame UV emission. Putting together all the measurements at z ∼ 5, spanning two decades in luminosity from LIR ∼ 1011 L⊙ to LIR ∼ 1013 L⊙, the data highlight a steeply increasing trend of the re, FIR − LIR relation at LIR < 1012 L⊙, followed by a downturn and a decreasing trend at brighter luminosities. Finally, simulations that extend up to the stellar masses of the ALPINE galaxies considered in the present work predict a subset of galaxies (∼25% at 1010 M⊙ < M⋆ < 1011 M⊙) with sizes as large as those measured.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".