RED NUGGETS AT<i>z</i>∼ 1.5: COMPACT PASSIVE GALAXIES AND THE FORMATION OF THE KORMENDY RELATION
Bibliographic record
Abstract
We present the results of Near-Infrared Camera and Multi-Object Spectrometer (NICMOS) imaging of a sample of 19 high-mass passively evolving galaxies with 1.2 < z < 2, taken primarily from the Gemini Deep Deep Survey (GDDS). Around 80% of galaxies in our GDDS sample have spectra dominated by stars with ages ≳1 Gyr. Our rest-frame R -band images show that most of these objects have compact regular morphologies which follow the classical R 1/4 law. These galaxies scatter along a tight sequence in the size versus surface brightness parameter space which defines the Kormendy relation. Around one-third (3/10) of the massive red objects in the GDDS sample are extraordinarily compact, with effective radii under 1 kpc. Our NICMOS observations allow the detection of such systems more robustly than is possible with optical (rest-frame UV) data, and while similar systems have been seen at z ≳ 2, this is the first time such systems have been detected in a rest-frame optical survey at 1.2 < z < 2. We refer to these compact galaxies as "red nuggets," and note that similarly compact massive galaxies are completely absent in the nearby universe. We introduce a new "stellar mass Kormendy relation" (stellar mass density versus size) which we use to single out the effects of size evolution from those of luminosity and color evolution in stellar populations. The 1 < z < 2 passive galaxies have mass densities that are an order of magnitude larger then early-type galaxies today and are comparable to the compact distant red galaxies at 2 < z < 3. We briefly consider mechanisms for size evolution in contemporary models focusing on equal-mass mergers and adiabatic expansion driven by stellar mass loss. Neither of these mechanisms appears to be able to transform the high-redshift Kormendy relation into its local counterpart, leaving the origin and fate of these compact "red nuggets" unresolved.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".