The effect of stellar feedback on a Milky Way-like galaxy and its gaseous halo
Bibliographic record
Abstract
We present the study of a set of N-body+SPH simulations of a Milky Way-like system produced by the radiative cooling of hot gas embedded in a dark matter halo. The galaxy and its gaseous halo evolve for 10 Gyr in isolation, which allows us to study how internal processes affect the evolution of the system. We show how the morphology, the kinematics and the evolution of the galaxy are affected by the input supernova feedback energy E$_{\rm SN}$, and we compare its properties with those of the Milky Way. Different values of E$_{\rm SN}$ do not significantly affect the star formation history of the system, but the disc of cold gas gets thicker and more turbulent as feedback increases. Our main result is that, for the highest value of E$_{\rm SN}$ considered, the galaxy shows a prominent layer of extra-planar cold (log(T)<4.3) gas extended up to a few kpc above the disc at column densities of $10^{19}$ cm$^{-2}$. The kinematics of this material is in agreement with that inferred for the HI halos of our Galaxy and NGC 891, although its mass is lower. Also, the location, the kinematics and the typical column densities of the hot (5.3
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".