Pre-heating the ICM in high resolution simulations: the effect on the gas entropy
Bibliographic record
Abstract
We present first results from high-resolution tree + smoothed particle hydrodynamics simulations of galaxy clusters and groups that are aimed at studying the effect of nongravitational heating on the entropy of the intracluster medium (ICM). We simulate three systems having emission-weighted temperatures T ew ≃ 0.6, 1, and 3 keV with spatial resolutions better than 1% of the virial radius. We consider the effect of different prescriptions for nongravitational ICM heating, such as supernova energy feedback, as predicted by semianalytical models of galaxy formation, and two different minimum entropy floors, S fl = 50 and 100 keV cm 2 , imposed at z = 3. Simulations with only gravitational heating nicely reproduce predictions from self-similar ICM models, while extra heating is shown to break the self-similarity, by a degree that depends on the total injected energy and on the cluster mass. We use the observational results on the excess entropy in central regions of galaxy systems to constrain the amount of extra heating required. We find that by setting the entropy floor S fl = 50 keV cm 2 , which corresponds to an extra heating energy of about 1 keV per particle, we are able to reproduce the observed excess of ICM entropy.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".