The abundance of (not just) dark matter haloes
Bibliographic record
Abstract
We study the effect of baryons on the abundance of structures and substructures in a Λ cold dark matter (CDM) cosmology, using a pair of high-resolution cosmological simulations from the Galaxies-Intergalactic Medium Interaction Calculation project. Both simulations use identical initial conditions, but while one contains only dark matter, the other also includes baryons. We find that gas pressure, reionization, supernova feedback, stripping and truncated accretion systematically reduce the total mass and the abundance of structures below ∼1012 M⊙ compared to the pure dark matter simulation. Taking this into account and adopting an appropriate detection threshold lower the abundance of observed galaxies with maximum circular velocities vmax < 100 km s−1, significantly reducing the reported discrepancy between ΛCDM and the measured H i velocity function of the Arecibo Legacy Fast ALFA survey. We also show that the stellar-to-total mass ratios of galaxies with stellar masses of ∼105–107 M⊙ inferred from abundance matching of the (sub)halo mass function to the observed galaxy mass function increase by a factor of ∼2. In addition, we find that an important fraction of low-mass subhaloes are completely devoid of stars. Accounting for the presence of dark subhaloes below 1010 M⊙ further reduces the abundance of observable objects and leads to an additional increase in the inferred stellar-to-total mass ratio by factors of 2–10 for galaxies in haloes of 109–1010 M⊙. This largely reconciles the abundance matching results with the kinematics of individual dwarf galaxies in ΛCDM. We propose approximate corrections to the masses of objects derived from pure dark matter calculations to account for baryonic effects.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".