The ATLAS3D project – XXI. Correlations between gradients of local escape velocity and stellar populations in early-type galaxies
Bibliographic record
Abstract
We explore the connection between the local escape velocity, Vesc, and the stellar population properties in the ATLAS3D survey, a complete, volume-limited sample of nearby early-type galaxies. We make use of ugriz photometry to construct Multi-Gaussian Expansion models of the surface brightnesses of our galaxies. We are able to fit the full range of surface brightness profiles found in our sample, and in addition we reproduce the results of state-of-the-art photometry in the literature with residuals of 0.04 mag. We utilize these photometric models and SAURON integral-field spectroscopy, combined with Jeans dynamical modelling, to determine the local Vesc derived from the surface brightness. We find that the local Vesc is tightly correlated with the Mg b and Fe5015 line strengths and optical colours, and anti-correlated with the Hβ line strength. In the case of the Mg b and colour–Vesc relations we find that the relation within individual galaxies follows the global relation between different galaxies. We intentionally ignored any uncertain contribution due to dark matter since we are seeking an empirical description of stellar population gradients in early-type galaxies that is ideal for quantitative comparison with model predictions. We also make use of single stellar population (SSP) modelling to transform our line strength index measurements into the SSP-equivalent parameters age (t), metallicity ([Z/H]) and α-enhancement [α/Fe]. The residuals from the relation are correlated with age, [α/Fe], molecular gas mass and local environmental density. We identify a population of galaxies that occur only at low Vesc that exhibit negative gradients in the Mg b– and Colour–Vesc relations. These galaxies typically have young central stellar populations and contain significant amounts of molecular gas and dust. Combining these results with N-body simulations of binary mergers we use the Mg b–Vesc relation to constrain the possible number of dry mergers experienced by the local early-type galaxy population – a typical massive early-type galaxy can have experienced only ∼1.5 major mergers before becoming a significant outlier in the Mg b–Vesc relation.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.025 |
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".