A Measurement of the Assembly of Milky Way Analogs at Redshifts 0.5 < z < 2 with Resolved Stellar Mass and Star Formation Rate Profiles
Bibliographic record
Abstract
Abstract The resolved mass assembly of Milky Way–mass galaxies has been previously studied in simulations, the local Universe, and at higher redshifts using infrared (IR) light profiles. To better characterize the mass assembly of Milky Way analogs (MWAs), as well as their changes in star formation rate (SFR) and color gradients, we construct resolved stellar mass and SFR maps of MWA progenitors selected with abundance matching techniques up to z ∼2 using deep, multiwavelength imaging data from the Hubble Frontier Fields. Our results using stellar mass profiles agree well with previous studies that utilize IR light profiles, showing that the inner 2 kpc of the galaxies and the regions beyond 2 kpc exhibit similar rates of stellar mass growth. This indicates the progenitors of MWAs from z ∼ 2 to the present do not preferentially grow their bulges or their disks. The evolution of the SFR profiles indicates a greater decrease in SFR density in the inner regions versus the outer regions. Sérsic parameters indicate modest growth in the central regions at lower redshifts, perhaps indicating slight bulge growth. However, the Sérsic index does not rise above n ∼ 2 until z < 0.5, meaning these galaxies are still disk-dominated systems. We find that the half-mass radii of the MWA progenitors increase between 1.5 < z < 2, but remain constant at later epochs (z < 1.5). This implies mild bulge growth since z ∼ 2 in MWA progenitors, in line with previous MWA mass assembly studies.
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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 | 0.000 |
| 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".