Do Cooling Flows Survive Cluster Mergers?
Bibliographic record
Abstract
We report the results of recent numerical simulations of the head-on merger of a cooling flow cluster with an infalling subcluster of galaxies. The objective of these simulations was to examine the effects of different types of cluster mergers (with 16 : 1 and 4 : 1 mass ratios) on the evolution of cluster cooling flows (with mass accretion rates of 100 and 400 M ☉ yr -1 ). The two-dimensional simulations were performed with a combined hydrodynamics/ N -body code on a uniform grid with a resolution of 20 kpc (~12 zones per core radius). In our simulations, cooling flow disruption is indicated by a dramatic increase (by a factor of 10-40) in the central cooling time of the primary cluster. We find that the ram pressure of the infalling gas is crucial in determining the fate of the cooling flow, because disruption occurs when a substantial amount of subcluster gas reaches the primary's core. In such cases, the subcluster gas can increase the central cooling time by displacing the high-density cooling gas and by heating it via shocks and turbulent gas motions. However, the fate of a merging cooling flow is also dependent on its initial cooling time. In cases where the initial cooling time is very short (i.e., 10-40 times shorter than the Hubble time), then even if the flow is disrupted, the central cooling time will remain less than a Hubble time, and the flow will likely reestablish itself. This has an important observational consequence, because such clusters will be classified as cooling flows on the basis of their cooling times, even though they have undergone a significant merger. In addition, we find that there is a time delay between core crossing and the point at which the central cooling time of a disrupted flow becomes of order a Hubble time. Thus, even in the case of disruption, a cluster can be classified as a cooling flow and exhibit substructure (indicative of a merger) for 1-2 Gyr after merging with a subcluster. We argue that our results make it possible to reconcile the high cooling flow frequency inferred by some observations with both high merger rates and a high frequency of substructure.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".