Coevolution of Brightest Cluster Galaxies and Their Host Clusters in IllustrisTNG
Bibliographic record
Abstract
Abstract We use IllustrisTNG simulations to explore the dynamic scaling relation between massive clusters and their—central—brightest cluster galaxies (BCGs). The IllustrisTNG-300 simulation we use includes 280 massive clusters from the z = 0 snapshot with M 200 > 1014 M ⊙, enabling a robust statistical analysis. We derive the line-of-sight velocity dispersion of the stellar particles of the BCGs (σ *,BCG), analogous to the observed BCG stellar velocity dispersion. We also compute the subhalo velocity dispersion to measure the cluster velocity dispersion (σ cl). Both σ *,BCG and σ cl are proportional to the cluster halo mass, but the slopes differ slightly. Thus, like the observed relation, σ *,BCG/σ cl declines as a function of σ cl, but the scatter is large. We explore the redshift evolution of the σ *,BCG − σ cl scaling relation for z ≲ 1 in a way that can be compared directly with observations. The scaling relation has a similar slope at high redshift, but the scatter increases because of the large scatter in σ *,BCG. The simulations imply that high-redshift BCGs are dynamically more complex than their low-redshift 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".