The dynamical state and mass–concentration relation of galaxy clusters
Bibliographic record
Abstract
We use the Millennium Simulation series to study how the dynamical state of dark matter haloes affects the relation between mass and concentration. We find that a large fraction of massive systems are identified when they are substantially out of equilibrium and in a particular phase of their dynamical evolution: the more massive the halo, the more likely it is found at a transient stage of high concentration. This state reflects the recent assembly of massive haloes and corresponds to the first pericentric passage of recently accreted material when, before virialization, the kinetic and potential energies reach maximum and minimum values, respectively. This result explains the puzzling upturn in the mass–concentration relation reported in recent work for massive haloes; indeed, the upturn disappears when only dynamically relaxed systems are considered in the analysis. Our results warn against applying simple equilibrium models to describe the structure of rare, massive galaxy clusters and urge caution when extrapolating scaling laws calibrated on lower mass systems, where such deviations from equilibrium are less common. The evolving dynamical state of galaxy clusters ought to be carefully taken into account if cluster studies are to provide precise cosmological constraints.
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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 | 0.007 |
| 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) | 0.002 | 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".