Gas infall and radial transport in cosmological simulations of milky way-mass discs
Bibliographic record
Abstract
ABSTRACT Observations indicate that a continuous supply of gas is needed to maintain observed star formation rates in large, discy galaxies. To fuel star formation, gas must reach the inner regions of such galaxies. Despite its crucial importance for galaxy evolution, how and where gas joins galaxies is poorly constrained observationally and rarely explored in fully cosmological simulations. To investigate gas accretion in the vicinity of galaxies at low redshift, we analyse the FIRE-2 cosmological zoom-in simulations for 4 Milky Way mass galaxies (Mhalo ∼ 1012M⊙), focusing on simulations with cosmic ray physics. We find that at z ∼ 0, gas approaches the disc with angular momentum similar to the gaseous disc edge and low radial velocities, piling-up near the edge and settling into full rotational support. Accreting gas moves predominately parallel to the disc and joins largely in the outskirts. Immediately prior to joining the disc, trajectories briefly become more vertical on average. Within the disc, gas motion is complex, being dominated by spiral arm induced oscillations and feedback. However, time and azimuthal averages show slow net radial infall with transport speeds of 1–3 km s−1 and net mass fluxes through the disc of ∼M⊙ yr−1, comparable to the galaxies’ star formation rates and decreasing towards galactic centre as gas is sunk into star formation. These rates are slightly higher in simulations without cosmic rays (1–7 km s−1, ∼4–5 M⊙ yr−1). We find overall consistency of our results with observational constraints and discuss prospects of future observations of gas flows in and around galaxies.
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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 | 0.001 |
| Open science | 0.001 | 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".