Disc flaring with TNG50: diversity across Milky Way and M31 analogues
Bibliographic record
Abstract
ABSTRACT We use the sample of 198 Milky Way (MW) and Andromeda (M31) analogues from TNG50 to quantify the level of disc flaring predicted by a modern, high-resolution cosmological hydrodynamical simulation. Disc flaring refers to the increase of vertical stellar disc height with galactocentric distance. The TNG50 galaxies are selected to have stellar discy morphology, a stellar mass in the range of M* = 1010.5–11.2 M⊙, and an MW-like Mpc-scale environment at z = 0. The stellar discs of such TNG50 MW/M31 analogues exhibit a wide diversity of structural properties, including a number of galaxies with disc scale length and thin and thick disc scale heights that are comparable to those measured or inferred for the Galaxy and Andromeda. With one set of physical ingredients, TNG50 returns a large variety of flaring flavours and amounts, also for mono-age stellar populations. With this paper, we hence propose a non-parametric characterization of flaring. The typical MW/M31 analogues exhibit disc scale heights that are 1.5–2 times larger in the outer than in the inner regions of the disc for both old and young stellar populations, but with a large galaxy-to-galaxy variation. Which stellar population flares more, and by how much, also varies from galaxy to galaxy. TNG50 de facto brackets existing observational constraints for the Galaxy and all previous numerical findings. A link between the amount of flaring and the z = 0 global galaxy structural properties or merger history is complex. However, a connection between the scale heights and the local stellar vertical kinematics and gravitational potential is clearly in place.
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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 | 0.001 |
| 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".