The origins of the circumgalactic medium in the FIRE simulations
Bibliographic record
Abstract
ABSTRACT We use a particle tracking analysis to study the origins of the circumgalactic medium (CGM), separating it into (1) accretion from the intergalactic medium (IGM), (2) wind from the central galaxy, and (3) gas ejected from other galaxies. Our sample consists of 21 FIRE-2 simulations, spanning the halo mass range Mh ∼ 1010–1012 M⊙, and we focus on z = 0.25 and z = 2. Owing to strong stellar feedback, only ∼L⋆ haloes retain a baryon mass $\gtrsim\! 50\hbox{ per cent}$ of their cosmic budget. Metals are more efficiently retained by haloes, with a retention fraction $\gtrsim\! 50\hbox{ per cent}$. Across all masses and redshifts analysed $\gtrsim \!60\hbox{ per cent}$ of the CGM mass originates as IGM accretion (some of which is associated with infalling haloes). Overall, the second most important contribution is wind from the central galaxy, though gas ejected or stripped from satellites can contribute a comparable mass in ∼L⋆ haloes. Gas can persist in the CGM for billions of years, resulting in well mixed-halo gas. Sightlines through the CGM are therefore likely to intersect gas of multiple origins. For low-redshift ∼L⋆ haloes, cool gas (T < 104.7 K) is distributed on average preferentially along the galaxy plane, however with strong halo-to-halo variability. The metallicity of IGM accretion is systematically lower than the metallicity of winds (typically by ≳1 dex), although CGM and IGM metallicities depend significantly on the treatment of subgrid metal diffusion. Our results highlight the multiple physical mechanisms that contribute to the CGM and will inform observational efforts to develop a cohesive picture.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".