<scp>TheThreeHundred</scp> Project: ram pressure and gas content of haloes and subhaloes in the phase-space plane
Bibliographic record
Abstract
We use TheThreeHundred project, a suite of 324 resimulated massive galaxy clusters embedded in a broad range of environments, to investigate (i) how the gas content of the surrounding haloes correlates with the phase-space position at |$z$| = 0 and (ii) the role that ram pressure plays in this correlation. By stacking all 324 normalized phase-space planes containing 169 287 haloes and subhaloes, we show that the halo gas content is tightly correlated with the phase-space position. At |${\sim }1.5\hbox{--}2\, {R}_{\text{200}}$| of the cluster dark matter halo, we find an extremely steep decline in the halo gas content of infalling haloes and subhaloes irrespective of cluster mass, possibly indicating the presence of an accretion shock. We also find that subhaloes are particularly gas-poor, even in the cluster outskirts, which could indicate active regions of ongoing pre-processing. By modelling the instantaneous ram pressure experienced by each halo and subhalo at |$z$| = 0, we show that the ram pressure intensity is also well correlated with the phase-space position, which is again irrespective of cluster mass. In fact, we show that regions in the phase-space plane with high differential velocity between a halo or subhalo and its local gas environment are almost mutually exclusive with high halo gas content regions. This suggests a causal link between the gas content of objects and the instantaneous ram pressure they experience, where the dominant factor is the differential velocity.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".