The Bimodal Galaxy Color Distribution: Dependence on Luminosity and Environment
Bibliographic record
Abstract
We analyze the u - r color distribution of 24,346 galaxies with M r ≤ -18 and z < 0.08, drawn from the Sloan Digital Sky Survey first data release, as a function of luminosity and environment. The color distribution is well fitted with two Gaussian distributions, which we use to divide the sample into a blue and red population. At fixed luminosity, the mean color of the blue (red) distribution is nearly independent of environment, with a weakly significant (~3 σ) detection of a trend for colors to become redder by 0.1-0.14 (0.03-0.06) mag with a factor of ~100 increase in local density, as characterized by the surface density of galaxies within a ±1000 km s -1 redshift slice. In contrast, at fixed luminosity the fraction of galaxies in the red distribution is a strong function of local density, increasing from ~10%-30% of the population in the lowest density environments to ~70% at the highest densities. The strength of this trend is similar for both the brightest (-23 < M r < -22) and faintest (-19 < M r < -18) galaxies in our sample. The fraction of red galaxies within the virialized regions of clusters shows no significant dependence on velocity dispersion. Even at the lowest densities explored, a substantial population of red galaxies exists, which might be fossil groups. We propose that most star-forming galaxies today evolve at a rate that is determined primarily by their intrinsic properties and independent of their environment. Any environmentally triggered transformations from blue to red colors must occur either on a short timescale or preferentially at high redshift to preserve the simple Gaussian nature of the color distribution. The mechanism must be effective for both bright and faint galaxies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 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".