Galaxy populations in the 26 most massive galaxy clusters in the South Pole Telescope SPT-SZ survey
Bibliographic record
Abstract
We present a study of the optical properties of the 26 most massive galaxy clusters within the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) 2500 deg2 survey spanning the redshift range 0.10 < z < 1.13. We measure the radial profiles, the luminosity functions (LFs), and the halo occupation numbers (HONs) using optical data of typical depth m* + 2. The stacked radial profiles are consistent with a Navarro–Frenk–White profile of concentration |$2.84^{+0.40}_{-0.37}$| for the red sequence (RS) and |$2.36^{+0.38}_{-0.35}$| for the total population. Stacking the data in multiple redshift bins shows slight redshift evolution in the concentration when both the total population is used, and when only RS galaxies are used (at 2.1σ and 2.8σ, respectively). The stacked LF shows a faint end slope |$\alpha = -1.06^{+0.04}_{-0.03}$| for the total and |$\alpha = -0.80^{+0.04}_{-0.03}$| for the RS population. The redshift evolution of m* is consistent with a passively evolving composite stellar population (CSP) model. Adopting the CSP model predictions, we explore the redshift evolution of the Schechter parameters α and ϕ*. We find α for the total population to be consistent with no evolution (0.3σ), and mildly significant evidence of evolution for the red galaxies (1.1–2.1σ). The data show that the density ϕ*/E2(z) decreases with redshift, in tension with the self-similar expectation at a 2.4σ level for the total population. The measured HON–mass relation has a lower normalization than previous low redshift studies. Finally, our data support HON redshift evolution at a 2.1σ level, with clusters at higher redshift containing fewer galaxies than their low-z counterparts.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".