Early-type galaxy density profiles from IllustrisTNG – III. Effects on outer kinematic structure
Bibliographic record
Abstract
ABSTRACT Early-type galaxies (ETGs) possess total density profiles close to isothermal, which can lead to non-Gaussian line-of-sight velocity dispersion (LOSVD) under anisotropic stellar orbits. However, recent observations of local ETGs in the MASSIVE Survey reveal outer kinematic structures at 1.5Reff (effective radius) that are inconsistent with fixed isothermal density profiles; the authors proposed varying density profiles as an explanation. We aim to verify this conjecture and understand the influence of stellar assembly on these kinematic features through mock ETGs in IllustrisTNG. We create mock Integral-Field-Unit observations to extract projected stellar kinematic features for 207 ETGs with stellar mass $M_{\ast }\geqslant 10^{11} \, \mathrm{M_{\odot}}$ in TNG100-1. The mock observations reproduce the key outer (1.5Reff) kinematic structures in the MASSIVE ETGs, including the puzzling positive correlation between velocity dispersion profile outer slope γouter and the kurtosis h4’s gradient. We find that h4 is uncorrelated with stellar orbital anisotropy beyond Reff; instead, we find that the variations in γouter and outer h4 (a good proxy for h4 gradient) are both driven by variations of the density profile at the outskirts across different ETGs. These findings corroborate the proposed conjecture and rule out velocity anisotropy as the origin of non-Gaussian outer kinematic structure in ETGs. We also find that the outer kurtosis and anisotropy correlate with different stellar assembly components, with the former related to minor mergers or flyby interactions while the latter is mainly driven by major mergers, suggesting distinct stellar assembly origins that decorrelates the two quantities.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".