STELLAR POPULATIONS OF HIGHLY MAGNIFIED LENSED GALAXIES: YOUNG STARBURSTS AT<i>z</i>∼ 2
Bibliographic record
Abstract
We present a comprehensive analysis of the rest-frame UV to near-IR spectral energy distributions (SEDs) and rest-frame optical spectra of four of the brightest gravitationally lensed galaxies in the literature: RCSGA 032727-132609 at z = 1.70, MS1512-cB58 at z = 2.73, SGAS J152745.1+065219 at z = 2.76, and SGAS J122651.3+215220 at z = 2.92. This includes new Spitzer imaging for RCSGA0327 as well as new spectra, near-IR imaging and Spitzer imaging for SGAS1527 and SGAS1226. Lensing magnifications of 3–4 mag allow a detailed study of the stellar populations and physical conditions. We compare star formation rates (SFRs) as measured from the SED fit, the Hα and [O ii ] λ3727 emission lines, and the UV+IR bolometric luminosity where 24 μm photometry is available. The SFR estimate from the SED fit is consistently higher than the other indicators, which suggests that the Calzetti dust extinction law used in the SED fitting is too flat for young star-forming galaxies at z ∼ 2. Our analysis finds similar stellar population parameters for all four lensed galaxies: stellar masses (3–7) × 10 9 M ☉ , young ages ∼100 Myr, little dust content E ( B − V ) = 0.10–0.25, and SFRs around 20–100 M ☉ yr −1 . Compared to typical values for the galaxy population at z ∼ 2, this suggests we are looking at newly formed, starbursting systems that have only recently started the buildup of stellar mass. These results constitute the first detailed, uniform analysis of a sample of the growing number of strongly lensed galaxies known at z ∼ 2.
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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 | 0.003 | 0.002 |
| 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".