The properties of ‘dark’ ΛCDM haloes in the Local Group
Bibliographic record
Abstract
We examine the baryon content of low-mass Λ cold dark matter (ΛCDM) haloes (108 < M200/M⊙ < 5 × 109) using the APOSTLE cosmological hydrodynamical simulations. Most of these systems are free of stars and have a gaseous content set by the combined effects of cosmic reionization, which imposes a mass-dependent upper limit, and of ram-pressure stripping, which reduces it further in high-density regions. Haloes mainly affected by reionization (RELHICs; REionization-Limited H i Clouds) inhabit preferentially low-density regions and make up a population where the gas is in hydrostatic equilibrium with the dark matter potential and in thermal equilibrium with the ionizing UV background. Their thermodynamic properties are well specified, and their gas density and temperature profiles may be predicted in detail. Gas in RELHICs is nearly fully ionized but with neutral cores that span a large range of H i masses and column densities and have negligible non-thermal broadening. We present predictions for their characteristic sizes and central column densities; the massive tail of the distribution should be within reach of future blind H i surveys. Local Group RELHICs (LGRs) have some properties consistent with observed Ultra Compact High Velocity Clouds (UCHVCs) but the sheer number of the latter suggests that most UCHVCs are not RELHICs. Our results suggest that LGRs (i) should typically be beyond 500 kpc from the Milky Way or M31; (ii) have positive Galactocentric radial velocities; (iii) H i sizes not exceeding 1 kpc, and (iv) should be nearly round. The detection and characterization of RELHICs would offer a unique probe of the small-scale clustering of CDM.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".