The Triangulum Extended (TREX) Survey: The Stellar Disk Dynamics of M33 as a Function of Stellar Age
Bibliographic record
Abstract
Abstract Triangulum (M33) is a low-mass, relatively undisturbed spiral galaxy that offers a new regime in which to test models of dynamical heating. In spite of its proximity, M33's dynamical heating history has not yet been well-constrained. In this work, we present the TREX Survey, the largest stellar spectroscopic survey across the disk of M33. We present the stellar disk kinematics as a function of age to study the past and ongoing dynamical heating of M33. We measure line-of-sight velocities for ∼4500 disk stars. Using a subset, we divide the stars into broad age bins using Hubble Space Telescope and Canada–France–Hawaii Telescope photometric catalogs: massive main-sequence stars and helium-burning stars (∼80 Myr), intermediate-mass asymptotic branch stars (∼1 Gyr), and low-mass red giant branch stars (∼4 Gyr). We compare the stellar disk dynamics to that of the gas using existing H i, CO, and Hα kinematics. We find that the disk of M33 has relatively low-velocity dispersion (∼16 km s−1), and unlike in the Milky Way and Andromeda galaxies, there is no strong trend in velocity dispersion as a function of stellar age. The youngest disk stars are as dynamically hot as the oldest disk stars and are dynamically hotter than predicted by most M33-like low-mass simulated analogs in Illustris. The velocity dispersion of the young stars is highly structured, with the large velocity dispersion fairly localized. The cause of this high-velocity dispersion is not evident from the observations and simulated analogs presented here.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".