PEARLS: Low Stellar Density Galaxies in the El Gordo Cluster Observed with JWST
Bibliographic record
Abstract
Abstract A full understanding of how unusually large ultradiffuse galaxies (UDGs) fit into our conventional theory of galaxy formation remains elusive, despite the large number of objects identified locally. A natural extension of UDG research is the study of similar galaxies at higher redshift to establish how their properties may evolve over time. However, this has been a challenging task given how severely systematic effects and cosmological surface brightness dimming inhibit our ability to analyze low surface brightness galaxies at high z. Here, we present a sample of low stellar surface density galaxies (LDGs) at moderate redshift, likely the progenitors of local UDGs, identified using deep near-IR observations of the El Gordo cluster at z = 0.87 with JWST. By stacking eight NIRCAM filters, we reach an apparent surface brightness sensitivity of 24.59 mag arcsec−2, which is faint enough to be complete to the bright end of the LDG population. Our analysis identifies significant differences between this population and UDGs observed locally, such as their color and size distributions, which suggest that the UDG progenitors at high z are bluer and more extended than UDGs at z = 0. This suggests that multiple mechanisms are responsible for the UDG formation and that prolonged transformation of cluster dwarfs is not a primary UDG formation mechanism at high z. Furthermore, we find a slight overabundance of LDGs in El Gordo, and, in contrast to findings in local clusters, our analysis does not show a deficit of LDGs in the center of El Gordo, implying that tidal destruction of LDGs is significant between z = 0.87 and z = 0.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".