ON THE CLUSTER PHYSICS OF SUNYAEV–ZEL’DOVICH AND X-RAY SURVEYS. IV. CHARACTERIZING DENSITY AND PRESSURE CLUMPING DUE TO INFALLING SUBSTRUCTURES
Bibliographic record
Abstract
Understanding the outskirts of galaxy clusters at the virial radius ( R 200 ) and beyond is critical for an accurate determination of cluster masses, structure growth, and to ensure unbiased cosmological parameter estimates from cluster surveys. This problem has drawn renewed interest due to recent determinations of gas mass fractions beyond R 200 , which appear to be considerably larger than the cosmic mean. Here, we use a large suite of cosmological hydrodynamical simulations to study the inhomogeneity of the intra-cluster medium and employ different variants of simulated physics, including radiative gas physics and thermal feedback by active galactic nuclei. We find that density and pressure clumping closely trace each other as a function of radius, but the bias on density remains on average within R 200 . At larger radii, clumping increases steeply due to the continuous infall of coherent structures that have not yet passed the accretion shock. Density and pressure clumping increase with cluster mass and redshift, which probes on average dynamically younger objects that are still in the process of assembling. The angular power spectra of gas density and pressure show that the clumping signal is dominated by large-scale cosmic filaments that reach from the cosmic web into the clusters, signaling the presence of gravitationally driven "super clumping." While the prolateness of the gravitational halo potential implies an approximate radial correlation of these gaseous large-scale structures, gas density and pressure lose coherence on small scales across different radii due to dissipative gas physics. In contrast, the angular power spectrum of dark matter shows an almost uniform size distribution due to unimpeded subhalos. We provide a synopsis of the radial dependence of the clusters' non-equilibrium measures (kinetic pressure support, ellipticity, and clumping) that all increase sharply beyond R 200 .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".