The Three Hundred Project: Connection between star formation quenching and dynamical evolution in and around simulated galaxy clusters
Bibliographic record
Abstract
ABSTRACT In this work, we combine the semi-analytic model of galaxy formation and evolution sag with the 102 relaxed simulated galaxy clusters from the three hundred project, and we study the link between the quenching of star formation (SF) and the physical processes that galaxies experience through their dynamical history in and around clusters. We classify galaxies in four populations based on their orbital history: recent and ancient infallers, and backsplash and neighbouring galaxies. We find that ∼85 per cent of the current population of quenched galaxies located inside the clusters are ancient infallers with low or null content of hot and cold gas. The fraction of quenched ancient infallers increases strongly between the first and second pericentric passage, due to the removal of hot gas by the action of ram-pressure stripping (RPS). The majority of them quenches after the first pericentric passage, but a non-negligible fraction needs a second passage, specially galaxies with $M_\star \le 10^{10.5} \, {\rm M_\odot }$. Recent infallers represent ∼15 per cent of the quenched galaxies located inside the cluster and, on average, they contain a high proportion of hot and cold gas; moreover, pre-processing effects are responsible for quenching the recent infallers prior to infall onto the main cluster progenitor. The ∼65 per cent of quenched galaxies located around clusters are backsplash galaxies, for which the combination of RPS acting during a pre-processing stage and inside the cluster is necessary for the suppression of SF in this population.
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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 | 0.003 |
| 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".