On the Kinematic Nature of Apparent Disks at High Redshifts: Local Counterparts are Not Dominated by Ordered Rotation but by Tangentially Anisotropic Random Motion
Bibliographic record
Abstract
Abstract It is not straightforward to physically interpret the apparent morphology of galaxies. Recent observations by the James Webb Space Telescope (JWST) revealed a dominant galaxy population at high redshifts (z > 2) that were visually classified as disks for their flattened shapes and/or exponential light profiles. The extensively accepted interpretation is that they are dynamically cold disks supported by bulk rotation. However, it is long known that flattened shapes and exponential profiles are not exclusive for rotating disk structure. To break degeneracy and assess the rotational support of typical high-z galaxies in the JWST samples, those with active star formation and stellar masses lg ( M ⋆ / M ⊙ ) ∼ 9 , we study the kinematics of their equal-mass counterparts at z = 0. While these local star-forming low-mass galaxies are photometrically similar to real dynamically cold disks, they are not supported by ordered rotation but primarily by random motion, and their flattened shapes result largely from tangential orbital anisotropy. Given the empirical and theoretical evidence that young galaxies are dynamically hotter at higher redshifts, our results suggest that the high-z JWST galaxies may not be cold disks but are dynamically warm/hot galaxies with flattened shapes driven by anisotropy. While both have low rotational support, local low-mass galaxies possess oblate shapes, contrasting the prolate shapes (i.e., cigar like) of low-mass systems at high redshifts. Such shape transition (prolate ⇒ oblate) indicates an associated change in orbital anisotropy (radial ⇒ tangential), with roots likely in the assembly of their host dark matter halos.
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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".