Hydrodynamic simulations of an isolated star-forming gas cloud in the Virgo cluster
Bibliographic record
Abstract
ABSTRACT We present a suite of three-dimensional, high-resolution hydrodynamic simulations that follow the evolution of a massive (107 M⊙) pressure-confined, star-forming neutral gas cloud moving through a hot intracluster medium (ICM). The main goal of the analysis is to get theoretical insight into the lifetimes and evolution of stellar systems like the recently discovered star-forming cloud SECCO 1 in the Virgo cluster of galaxies, but it may be of general interest for the study of the star-forming gas clumps that are observed in the tails of ram pressure stripped galaxies. Building up on a previous, simple simulation, we explored the effect of different relative velocity of the cloud and larger temperature of the ICM, as well as the effect of the cloud self-gravity. Moreover, we performed a simulation including star formation and stellar feedback, allowing for a first time a direct comparison with the observed properties of the stars in the system. The survivability of the cold gas in the simulated clouds is granted on time-scales of the order of 1 Gyr, with final cold gas fractions generally >0.75. In all cases, the simulated systems end up, after 1 Gyr of evolution, as symmetric clouds in pressure equilibrium with the external hot gas. We also confirm that gravity played a negligible role at the largest scales on the evolution of the clouds. In our simulation with star formation, star formation begins immediately, it peaks at the earliest times, and decreases monotonically with time. Inhomogeneous supernova explosions are the cause of an asymmetric shape of the gas cloud, facilitating the development of instabilities and the decrease of the cold gas fraction.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".