Stellar mass function of cluster galaxies at<i>z</i>~ 1.5: evidence for reduced quenching efficiency at high redshift
Bibliographic record
Abstract
We present the stellar mass functions (SMFs) of passive and star-forming galaxies with a limiting mass of 1010.1M⊙ in four spectroscopically confirmed Spitzer Adaptation of the Red-sequence Cluster Survey (SpARCS) galaxy clusters at 1.37 <z< 1.63. The clusters have 113 spectroscopically confirmed members combined, with 8–45 confirmed members each. We construct Ks-band-selected photometric catalogs for each cluster with an average of 11 photometric bands ranging from u to 8 μm. We compare our cluster galaxies to a field sample derived from a similar Ks-band-selected catalog in the UltraVISTA/COSMOS field. The SMFs resemble those of the field, but with signs of environmental quenching. We find that 30 ± 20% of galaxies that would normally be forming stars in the field are quenched in the clusters. The environmental quenching efficiency shows little dependence on projected cluster-centric distance out to ~4 Mpc, providing tentative evidence of pre-processing and/or galactic conformity in this redshift range. We also compile the available data on environmental quenching efficiencies from the literature, and find that the quenching efficiency in clusters and in groups appears to decline with increasing redshift in a manner consistent with previous results and expectations based on halo mass growth.
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 | 0.000 |
| Scholarly communication | 0.000 | 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".