THE WiggleZ DARK ENERGY SURVEY: GALAXY EVOLUTION AT 0.25 ⩽<i>z</i>⩽ 0.75 USING THE SECOND RED-SEQUENCE CLUSTER SURVEY
Bibliographic record
Abstract
We study the evolution of galaxy populations around the spectroscopic WiggleZ sample of star-forming galaxies at 0.25 ⩽ z ⩽ 0.75 using the photometric catalog from the Second Red-Sequence Cluster Survey (RCS2). We probe the optical photometric properties of the net excess neighbor galaxies. The key concept is that the marker galaxies and their neighbors are located at the same redshift, providing a sample of galaxies representing a complete census of galaxies in the neighborhood of star-forming galaxies. The results are compared with those using the RCS WiggleZ Spare-Fibre (RCS-WSF) sample as markers, representing galaxies in cluster environments at 0.25 ⩽ z ⩽ 0.45. By analyzing the stacked color–color properties of the WiggleZ neighbor galaxies, we find that their optical colors are not a strong function of indicators of star-forming activities such as EW([O ii ]) or Galaxy Evolution Explorer ( GALEX ) near-UV luminosity of the markers. The galaxies around the WiggleZ markers exhibit a bimodal distribution on the color–magnitude diagram, with most of them located in the blue cloud. The optical galaxy luminosity functions (GLFs) of the blue neighbor galaxies have a faint-end slope α of ∼ − 1.3, similar to that for galaxies in cluster environments drawn from the RCS-WSF sample. The faint-end slope of the GLF for the red neighbors, however, is ∼ − 0.4, significantly shallower than the ∼ − 0.7 found for those in cluster environments. This suggests that the buildup of the faint end of the red sequence in cluster environments is in a significantly more advanced stage than that in the star-forming and lower galaxy density WiggleZ neighborhoods. We find that the red galaxy fraction ( f red ) around the star-forming WiggleZ galaxies has similar values from z ∼ 0.3 to z ∼ 0.6 with f red ∼ 0.28, but drops to f red ∼ 0.20 at z ≳ 0.7. This change of f red with redshift suggests that there is either a higher rate of star-forming galaxies entering the luminosity-limited sample at z ≳ 0.7, or a decrease in the quenching rate of star formation at that redshift. Comparing to that in a dense cluster environment, the f red of the WiggleZ neighbors is both considerably smaller and has a more moderate change with redshift, pointing to the stronger and more prevalent environmental influences on galaxy evolution in high-density regions.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".