Ionised gas kinematics and dynamical masses of <i>z</i> ≳ 6 galaxies from JADES/NIRSpec high-resolution spectroscopy
Bibliographic record
Abstract
We explore the kinematic gas properties of six 5.5 < z < 7.4 galaxies in the JWST Advanced Deep Extragalactic Survey (JADES), using high-resolution JWST/NIRSpec multi-object spectroscopy of the rest-frame optical emission lines [O III ] and H α . The objects are small and of low stellar mass (∼1 kpc; M * ∼ 10 7 − 9 M ⊙ ), less massive than any galaxy studied kinematically at z > 1 thus far. The cold gas masses implied by the observed star formation rates are about ten times higher than the stellar masses. We find that their ionised gas is spatially resolved by JWST, with evidence for broadened lines and spatial velocity gradients. Using a simple thin-disc model, we fit these data with a novel forward-modelling software that accounts for the complex geometry, point spread function, and pixellation of the NIRSpec instrument. We find the sample to include both rotation- and dispersion-dominated structures, as we detect velocity gradients of v ( r e )∼100 − 150 km s −1 , and we find velocity dispersions of σ 0 ∼ 30 − 70 km s −1 that are comparable to those at cosmic noon. The dynamical masses implied by these models ( M dyn ∼ 10 9 − 10 M ⊙ ) are higher than the stellar masses by up to a factor 40, and they are higher than the total baryonic mass (gas + stars) by a factor of ∼3. Qualitatively, this result is robust even if the observed velocity gradients reflect ongoing mergers rather than rotating discs. Unless the observed emission line kinematics is dominated by outflows, this implies that the centres of these galaxies are dominated by dark matter or that star formation is three times less efficient, leading to higher inferred gas masses.
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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 | 0.000 |
| 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".