Correcting the rotation curve of spiral galaxies for the non-circular motions induced by a bar
Bibliographic record
Abstract
The mass distribution of disk galaxies is usually determined through the use of rotation curves. This determination relies on two key assumptions; that the gas moves on circular orbits and that this motion traces the underlying gravitational potential. In the case of barred spiral galaxies the first assumption is false as the bar induces non-circular streaming motions in the gas. Therefore, the rotation curves of barred galaxies need to be corrected for the non-circular motions before being used for mass model analysis. In this dissertation, we use numerical simulations to quantify and correct for the non-circular flows induced by a bar. The aim is to investigate and quantify the effect of the bar properties on the amplitude of the non-circular motions. This is done by comparing the observational data such as rotation curves and bar properties with the kinematics and bar properties obtained from mocked galaxies. In chapter III, we examine the performance of ROTCUR and DISKFIT for deriving rotation curves from velocity maps of barred spiral galaxies using mock observations. Our results confirm that ROTCUR under-/overestimates measured rotation curves if the bar is aligned with one of the symmetry axes. The DISKFIT algorithm, which is specifically designed for barred galaxies only works for galaxies of intermediate bar orientations. In chapter IV, we quantify the magnitude of the non-circular flows and constraint the range of bar orientation angles where DiskFit fails by using Tree-SPH simulations from the GalMer database by Chilingarian et al . (2010 ). We found that the rotation curve obtained from ROTCUR was 40% smaller/larger than the expected velocities calculated from the gravitational potential when the bar is aligned with the major/minor axis. For the DISKFIT analysis, we found that DiskFit produces unrealistic values for all the models when the bar is within ten degrees of the symmetry axes. New hydrodynamic simulations of three disc galaxies (NGC 1300 , NGC 1530 and NGC 3621 ) are presented in chapter IV. Our objective is to create more realistic simulated galaxies that replicate the bar properties and velocity elds of the galaxies of our sample. The initial conditions for our simulations are determined through a Bayesian analysis of the azimuthally averaged rotation curve, the stellar surface brightness, and the gas surface density. The parameters posterior distribution functions (PDFs) combine with the disc stability parameters PDFs are used as criterion to select the model parameters. The velocities of the gas particles are transformed into velocity maps and compared with the observed galaxies. We are able to reproduce the bar properties and kinematics of the three galaxies in our sample. These findings imply that a tailored simulation is an effective way of investigating non-circular flows in disc galaxies especially when the bar orientation is close to the minor or major kinematical axis of the galaxy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.001 |
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".