A Revised Model for the Formation of Disk Galaxies: Low Spin and Dark Halo Expansion
Bibliographic record
Abstract
We use observed rotation velocity-luminosity ( VL ) and size-luminosity ( RL ) relations to single out a specific scenario for disk galaxy formation in the ΛCDM cosmology. Our model involves four independent lognormal random variables: dark halo concentration c , disk spin λ gal , disk mass fraction m gal , and stellar mass-to-light ratio ϒ I . A simultaneous match of the VL and RL zero points with adiabatic contraction requires low- c halos, but this model has V 2.2 ~ 1.8 V vir (where V 2.2 and V vir are the circular velocity at 2.2 disk scale lengths and the virial radius, respectively), which will be unable to match the luminosity function (LF). Similarly models without adiabatic contraction but standard c also predict high values of V 2.2 / V vir . Models in which disk formation induces an expansion rather than the commonly assumed contraction of the dark matter halos have V 2.2 ~ 1.2 V vir , which allows a simultaneous fit of the LF. This may result from nonspherical, clumpy gas accretion, where dynamical friction transfers energy from the gas to the dark matter. This model requires low λ gal and m gal values, contrary to naive expectations. However, the low λ gal is consistent with the notion that disk galaxies predominantly survive in halos with a quiet merger history, while a low m gal is also indicated by galaxy-galaxy lensing. The smaller than expected scatter in the RL relation and the lack of correlation between the residuals of the VL and RL relations, respectively, imply that the scatter in λ gal and in c needs to be smaller than predicted for ΛCDM halos, again consistent with the idea that disk galaxies preferentially reside in halos with a quiet merger history.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".