Spatially resolved gas and stellar kinematics in compact starburst galaxies
Bibliographic record
Abstract
Context.The kinematics of galaxies provide valuable insights into their physics and assembly history. Kinematics are governed not only by the gravitational potential, but also by merger events and stellar feedback processes such as stellar winds and supernova explosions. Aims.We aim to identify what governs the kinematics in a sample of SDSS-selected nearby starburst galaxies, by obtaining spatially resolved measurements of the gas and stellar kinematics. Methods.We obtained near-infrared integral-fieldK-band spectroscopy with VLT/SINFONI for 15 compact starburst galaxies. We derived the integrated as well as spatially resolved stellar and gas kinematics. The stellar kinematics were derived from the CO absorption bands, and Paαand Brγemission lines were used for the gas kinematics. Results.Based on the integrated spectra, we find that the majority of galaxies have gas and stellar velocity dispersion that are comparable. A spatially resolved comparison shows that the six galaxies that deviate show evidence for a bulge or stellar feedback. Two galaxies are identified as mergers based on their double-peaked emission lines. In our sample, we find a negative correlation between the ratio of the rotational velocity over the velocity dispersion (vrot/σ) and the star formation rate surface density. Conclusions.We propose a scenario where the global kinematics of the galaxies are determined by gravitational instabilities that affect both the stars and gas. This process could be driven by mergers or accretion events. Effects of stellar feedback on the ionised gas are more localised and detected only in the spatially resolved analysis. The mass derived from the velocity dispersion provides a reliable mass even if the galaxy cannot be spatially resolved. The technique used in this paper is applicable to galaxies at low and high redshift with the next generation of infrared-focussed telescopes (JWST and ELT).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".