Compact high-redshift galaxies are the cores of the most massive present-day spheroids
Bibliographic record
Abstract
Observations suggest that the effective radii of high-redshift massive spheroids are as much as a factor of ∼6 smaller than low-redshift galaxies of comparable mass. Given the apparent absence of low-redshift counterparts, this has often been interpreted as indicating that the high-density, compact red galaxies must be ‘puffed up’ by some mechanism. We compare the ensemble of high-redshift observations with large samples of well-observed, low-redshift ellipticals. At the same physical radii, the stellar surface mass densities of low- and high-redshift systems are comparable. Moreover, the abundance of high surface density material at low redshift is comparable to or larger than that observed at z > 1–2, consistent with the continuous buildup of spheroids over this time. The entire population of compact, high-redshift red galaxies may be the progenitors of the high-density cores of present-day ellipticals, with no need for a decrease in stellar density from z= 2 to 0. The primary difference between low- and high-redshift systems is thus the observed low-density material at large radii in low-redshift spheroids (rather than the high-density material in high-redshift spheroids). Such low-density material may either (1) assemble at z < 2 or (2) be present, but not yet detected, at z > 2. Mock observations of low-redshift massive systems suggest that the amount of low-density material at high redshifts is indeed significantly less than that at z= 0. However, deeper observations will be important in constraining the exact amount (or lack thereof) and distribution of this material, and how it builds up with redshift. We show that, without deep observations, the full extent of such material even at low redshifts can be difficult to determine, in particular if the mass profile is not exactly a single Sersic profile. We discuss the implications of our results for physical models of galaxy evolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
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".