Dust-penetrated arm classes: insights from rising and falling rotation curves
Bibliographic record
Abstract
In the last decade, near-infrared imaging has highlighted the decoupling of gaseous and old stellar discs: the morphologies of optical (Population I) tracers compared to the old stellar disc morphology, can be radically different. Galaxies which appear multi-armed and even flocculent in the optical may show significant grand-design spirals in the near-infrared. Furthermore, the optically determined Hubble classification scheme does not provide a sound way of classifying dust-penetrated stellar discs: spiral arm pitch angles (when measured in the near-infrared) do not correlate with Hubble type. The dust-penetrated classification scheme of Block & Puerari provides an alternative classification based on near-infrared morphology, which is thus more closely linked to the dominant stellar mass component. Here we present near-infrared K-band images of 14 galaxies, on which we have performed a Fourier analysis of the spiral structure in order to determine their near-infrared pitch angles and dust-penetrated arm classes. We have also used the rotation curve data of Mathewson et al. to calculate the rates of shear in the stellar discs of these galaxies. We find a correlation between near-infrared pitch angle and rate of shear: galaxies with wide open arms (the γ class) are found to have rising rotation curves, while those with falling rotation curves belong to the tightly wound α bin. The major determinant of near-infrared spiral arm pitch angle is the distribution of matter within the galaxy concerned. The correlation reported in this study provides the physical basis underpinning spiral arm classes in the dust-penetrated regime and underscores earlier spectroscopic findings by Burstein and Rubin that Hubble type and mass distributions are unrelated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".