Probing the CGM of low-redshift dwarf galaxies using FIRE simulations
Bibliographic record
Abstract
ABSTRACT Observations of ultraviolet (UV) metal absorption lines have provided insight into the structure and composition of the circumgalactic medium (CGM) around galaxies. We compare these observations with the low-redshift (z ≤ 0.3) CGM around dwarf galaxies in high-resolution cosmological zoom-in runs in the FIRE-2 (Feedback In Realistic Environments) simulation suite. We select simulated galaxies that match the halo mass, stellar mass, and redshift of the observed samples. We produce absorption measurements using trident for UV transitions of C iv, O vi, Mg ii, and Si iii. The FIRE equivalent width (EW) distributions and covering fractions for the C iv ion are broadly consistent with observations inside 0.5Rvir, but are underpredicted for O vi, Mg ii, and Si iii. The absorption strengths of the ions in the CGM are moderately correlated with the masses and star formation activity of the galaxies. The correlation strengths increase with the ionization potential of the ions. The structure and composition of the gas from the simulations exhibit three zones around dwarf galaxies characterized by distinct ion column densities: the discy interstellar medium, the inner CGM (the wind-dominated regime), and the outer CGM (the IGM accretion-dominated regime). We find that the outer CGM in the simulations is nearly but not quite supported by thermal pressure, so it is not in hydrostatic equilibrium, resulting in halo-scale bulk inflow and outflow motions. The net gas inflow rates are comparable to the star formation rate of the galaxy, but the bulk inflow and outflow rates are greater by an order of magnitude, with velocities comparable to the virial velocity of the halo. These roughly virial velocities (${\sim } 100 \, \rm km\, s^{-1}$) produce large EWs in the simulations. This supports a picture for dwarf galaxies in which the dynamics of the CGM at large scales are coupled to the small-scale star formation activity near the centre of their haloes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".