Resolved Mass Assembly and Star Formation in Milky Way Progenitors since <i>z</i> = 5 from JWST/CANUCS: From Clumps and Mergers to Well-ordered Disks
Bibliographic record
Abstract
Abstract We present a resolved study of 877 progenitors of Milky Way Analogs (MWAs) at 0.3 < z < 5, selected with abundance matching in the 10 fields of the Canadian NIRISS Unbiased Cluster Survey. Utilizing 18–21 bands of deep NIRCam, NIRISS, and Hubble Space Telescope photometry, we create resolved stellar mass maps and star formation rate (SFR) maps via spectral energy distribution fitting with Dense Basis. We examine their resolved stellar mass and specific SFR (sSFR) profiles as a function of galactocentric radius and find clear evidence for inside-out mass assembly. The total M ⋆ of the inner 2 kpc regions of the progenitors remains roughly constant (10 9.3−9.4 M ⊙ ) at 2 < z < 5, while the total M ⋆ of the regions beyond 2 kpc increases by 0.8 dex, from 10 7.5 M ⊙ to 10 8.3 M ⊙ . Additionally, the sSFRs of the outer regions increase with decreasing redshift, until z ∼ 2. The median Sérsic index of the MWA progenitors stays nearly constant at n ∼ 1 at 2 < z < 5, while the half-mass radii of their stellar mass profiles double. We perform additional morphological measurements on the stellar mass maps via the Gini-M20 plane and asymmetry parameters. They show that the rate of double-peak mergers and disturbances to galaxy structure also increases with redshift, with ∼50% of galaxies at 4 < z < 5 classified as disturbed and ∼20% classified as ongoing mergers. Overall, the early evolution of MWAs is revealed as chaotic, with significant mergers and high SFRs. Mass growth is primarily inside-out and galaxies become more disklike after z = 3.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".