The Origin of Star Formation Gradients in Rich Galaxy Clusters
Bibliographic record
Abstract
We examine the origin of clustercentric gradients in the star formation rates and colors of rich cluster galaxies within the context of a simple model where clusters are built through the ongoing accretion of field galaxies. The model assumes that after galaxies enter the cluster their star formation rates decline on a timescale of a few gigayears, the typical gas consumption timescale of disk galaxies in the field. Such behavior might be expected if tides and ram pressure strip off the gaseous envelopes that normally fuel star formation in spirals over a Hubble time. Combining these timescales with mass accretion histories derived from N -body simulations of cluster formation in a ΛCDM universe, we reproduce the systematic differences observed in the color distribution of cluster and field galaxies, as well as the strong suppression of star formation in cluster galaxies and its dependence on clustercentric radius. The simulations also indicate that a significant fraction of galaxies beyond the virial radius of the cluster may have been within the main body of the cluster in the past, a result that explains naturally why star formation in the outskirts of clusters (and as far out as 2 virial radii) is systematically suppressed relative to the field. The agreement with the data beyond the cluster virial radius is also improved if we assume that stripping happens within lower mass systems, before the galaxy is accreted into the main body of the cluster. We conclude that the star formation rates of cluster galaxies depend primarily on the time elapsed since their accretion onto massive virialized systems and that the cessation of star formation may have taken place gradually over a few gigayears.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".