Diffuse coronae in cosmological simulations of milky way-sized galaxies
Bibliographic record
Abstract
We investigate the properties of halo gas using three cosmological “zoom-in” simulations of realistic Milky Way-galaxy analogs with varying sub-grid physics. In all three cases, the mass of hot (T > 106 K) halo gas is ˜1% of the host's virial mass. The X-ray luminosity of two of the runs is consistent with observations of the Milky Way, while the third simulation is X-ray bright and resembles more closely a very massive, star-forming spiral. Hot halos extend to 140 kpc from the galactic center and are surrounded by a bubble of warm-hot (T={10}5-{10}6 K) gas that extends to the virial radius. Simulated halos agree well outside 20-30 kpc with the β-model of Miller & Bregman based on O vii absorption and O viii emission measurements. Warm-hot and hot gas contribute up to 80% of the total gas reservoir, and contain nearly the same amount of baryons as the stellar component. The mass of warm-hot and hot components falls into the range estimated for {L}* galaxies. With key observational constraints on the density of the Milky Way corona being satisfied, we show that concealing of the ubiquitous warm-hot baryons, along with the ejection of just 20%-30% of the diffuse gas out of the potential wells by supernova-driven outflows, can solve the “missing baryon problem.” The recovered baryon fraction within 3 virial radii is 90% of the universal value. With a characteristic density of ˜10-4 cm-3 at 50-80 kpc, diffuse coronae meet the requirement for fast and complete ram-pressure stripping of the gas reservoirs in dwarf galaxy satellites.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".