What galaxy masses perturb the local cosmic expansion?
Bibliographic record
Abstract
Abstract We use 12 cosmological N-body simulations of Local Group systems (the apostle models) to inspect the relation between the virial mass of the main haloes (Mvir,1 and Mvir,2), the mass derived from the relative motion of the halo pair (Mtim), and that inferred from the local Hubble flow (Mlhf). We show that within the spherical collapse model (SCM), the correspondence between the three mass estimates is exact, i.e. Mlhf = Mtim = Mvir,1 + Mvir,2. However, comparison with apostle simulations reveals that, contrary to what the SCM states, a relatively large fraction of the mass that perturbs the local Hubble flow and drives the relative trajectory of the main galaxies is not contained within Rvir, and that the amount of ‘extravirial’ mass tends to increase in galaxies with a slow accretion rate. In contrast, modelling the peculiar velocities around the Local Group returns an unbiased constraint on the virial mass ratio of the main galaxy pair. Adopting the outer halo profile found in N-body simulations, which scales as ρ ∼ R−4 at R ≳ Rvir, indicates that the galaxy masses perturbing the local Hubble flow roughly correspond to the asymptotically convergent (total) masses of the individual haloes. We show that estimates of Mvir based on the dynamics of tracers at R ≫ Rvir require a priori information on the internal matter distribution and the growth rate of the main galaxies, both of which are typically difficult to quantify.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".