The connection between the peaks in velocity dispersion and star-forming clumps of turbulent galaxies
Bibliographic record
Abstract
We present Keck/OSIRIS (OH Suppressing Infrared Imaging Spectrograph) adaptive optics observations with 150–400 pc spatial sampling of seven turbulent, clumpy disc galaxies from the DYnamics of Newly-Assembled Massive Objects (DYNAMO) sample (0.07 < z < 0.2). DYNAMO galaxies have previously been shown to be well matched in properties to main-sequence galaxies at z ∼ 1.5. Integral field spectroscopy observations using adaptive optics are subject to a number of systematics including a variable point spread function and spatial sampling, which we account for in our analysis. We present gas velocity dispersion maps corrected for these effects, and confirm that DYNAMO galaxies do have high gas velocity dispersion (σ = 40–80 km s−1), even at high spatial sampling. We find statistically significant structure in six out of seven galaxies. The most common distance between the peaks in velocity dispersion (σpeaks) and emission line peaks is ∼0.5 kpc; we note this is very similar to the average size of a clump measured with Hubble Space Telescope H α maps. This could suggest that σpeaks in clumpy galaxies likely arise due to some interaction between the clump and the surrounding interstellar medium of the galaxy, though our observations cannot distinguish between outflows, inflows or velocity shear. Observations covering a wider area of the galaxies will be needed to confirm this result.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".