Bibliographic record
Abstract
I highlight recent progress in our understanding of the origin of disk galaxy scaling laws in a hierarchically clustering universe. Numerical simulations of galaxy formation in Cold Dark Matter (CDM) dominated universes indicate that the slope and scatter of the I-band Tully-Fisher (TF) relation are well reproduced in this model, although not, as proposed in recent work, because of the cosmological equivalence between halo mass and circular velocity, but rather as a result of the dynamical response of the halo to the assembly of the luminous component of the galaxy. The zero-point of the TF relation is determined mainly by the stellar mass-to-light ratio ($Υ_I$) as well as by the concentration ($c$) of the dark halo. For $c \sim 10$, as is typical of halos formed in the ``concordance'' $Λ$CDM model, we find that this requires $Υ_I \sim 1.5$, in reasonable agreement with the mass-to-light ratios expected of stellar populations with colors similar to those of TF galaxies. This conclusion supersedes that of Navarro & Steinmetz (2000a,b), who claimed the $Λ$CDM halos were too concentrated to be consistent with the observed TF relation. The disagreement can be traced to inconsistencies in the normalization of the power spectrum used in that work. Our new results show that simulated disk galaxies in the $Λ$CDM scenario are not clearly inconsistent with the observed I-band Tully-Fisher relation. On the other hand,their angular momenta is much lower than observed. Accounting simultaneously for the spin, size and luminosity of disk galaxies remains a challenge for hierarchical models of galaxy formation.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".