DISK GALAXY SCALING RELATIONS IN THE SFI++: INTRINSIC SCATTER AND APPLICATIONS
Bibliographic record
Abstract
We study the scaling relations between the luminosities, sizes, and rotation velocities of disk galaxies in the SFI++, with a focus on the size–luminosity ( RL ) and size–rotation velocity ( RV ) relations. Using isophotal radii instead of disk scale lengths as a size indicator, we find relations that are significantly tighter than previously reported: the correlation coefficients of the template RL and RV relations are r = 0.97 and r = 0.85, respectively, which rival that of the more widely studied LV (Tully–Fisher) relation. The scatter in the SFI++ RL relation is 2.5–4 times smaller than previously reported for various samples, which we attribute to the reliability of isophotal radii relative to disk scale lengths. After carefully accounting for all measurement errors, our scaling relation error budgets are consistent with a constant intrinsic scatter in the LV and RV relations for velocity widths log W ≳ 2.4, with evidence for increasing intrinsic scatter below this threshold. The scatter in the RL relation is consistent with constant intrinsic scatter that is biased by incompleteness at the low- L end. Possible applications of the unprecedentedly tight SFI++ RV and RL relations are investigated. Just like the Tully–Fisher relation, the RV relation can be used as a distance indicator: we derive distances to galaxies with primary Cepheid distances that are accurate to 25%, and reverse the problem to measure a Hubble constant H 0 = 72 ± 7 km s −1 Mpc −1 . Combining the small intrinsic scatter of our RL relation ( int = 0.034 ± 0.001log [ h −1 kpc]) with a simple model for disk galaxy formation, we find an upper limit in the range of disk spin parameters that is a factor of ∼7 smaller than that of the halo spin parameters predicted by cosmological simulations. This likely implies that the halos hosting Sc galaxies have a much narrower distribution of spin parameters than previously thought.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".