Estimating non-circular motions in barred galaxies using numerical<i>N</i>-body simulations
Bibliographic record
Abstract
The observed velocities of the gas in barred galaxies are a combination of the azimuthally averaged circular velocity and non-circular motions, primarily caused by gas streaming along the bar. These non-circular flows must be accounted for before the observed velocities can be used in mass modelling. In this work, we examine the performance of the tilted-ring method and the diskfit algorithm for transforming velocity maps of barred spiral galaxies into rotation curves (RCs) using simulated data. We find that the tilted-ring method, which does not account for streaming motions, under-/overestimates the circular motions when the bar is parallel/perpendicular to the projected major axis. diskfit, which does include streaming motions, is limited to orientations where the bar is not aligned with either the major or minor axis of the image. Therefore, we propose a method of correcting RCs based on numerical simulations of galaxies. We correct the RC derived from the tilted-ring method based on a numerical simulation of a galaxy with similar properties and projections as the observed galaxy. Using observations of NGC 3319, which has a bar aligned with the major axis, as a test case, we show that the inferred mass models from the uncorrected and corrected RCs are significantly different. These results show the importance of correcting for the non-circular motions and demonstrate that new methods of accounting for these motions are necessary as current methods fail for specific bar alignments.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".