The Three Hundred project: The relationship between the shock and splashback radii of simulated galaxy clusters
Bibliographic record
Abstract
Abstract Observations of the intracluster medium (ICM) in the outskirts of galaxy clusters reveal shocks associated with gas accretion from the cosmic web. Previous work based on non-radiative cosmological hydrodynamical simulations have defined the shock radius, $r_{\text{shock}}$ , using the ICM entropy, $K \propto T/{n_\mathrm{e}}^{2/3}$ , where T and $n_{\text{e}}$ are the ICM temperature and electron density, respectively; the $r_{\text{shock}}$ is identified with either the radius at which K is a maximum or at which its logarithmic slope is a minimum. We investigate the relationship between $r_{\text{shock}}$ , which is driven by gravitational hydrodynamics and shocks, and the splashback radius, $r_{\text{splash}}$ , which is driven by the gravitational dynamics of cluster stars and dark matter and is measured from their mass profile. Using 324 clusters from The Three Hundred project of cosmological galaxy formation simulations, we quantify statistically how $r_{\text{shock}}$ relates to $r_{\text{splash}}$ . Depending on our definition, we find that the median $r_{\text{shock}} \simeq 1.38 r_{\text{splash}} (2.58 R_{200})$ when K reaches its maximum and $r_{\text{shock}} \simeq 1.91 r_{\text{splash}} (3.54 R_{200})$ when its logarithmic slope is a minimum; the best-fit linear relation increases as $r_{\text{shock}} \propto 0.65 r_{\text{splash}}$ . We find that $r_{\text{shock}}/R_{200}$ and $r_{\text{splash}}/R_{200}$ anti-correlate with virial mass, $M_{200}$ , and recent mass accretion history, and $r_{\text{shock}}/r_{\text{splash}}$ tends to be larger for clusters with higher recent accretion rates. We discuss prospects for measuring $r_{\text{shock}}$ observationally and how the relationship between $r_{\text{shock}}$ and $r_{\text{splash}}$ can be used to improve constraints from radio, X-ray, and thermal Sunyaev-Zeldovich surveys that target the interface between the cosmic web and clusters.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".