The ATLAS3D project – XV. Benchmark for early-type galaxies scaling relations from 260 dynamical models: mass-to-light ratio, dark matter, Fundamental Plane and Mass Plane
Bibliographic record
Abstract
We study the volume-limited and nearly mass selected (stellar mass M>6*10^9 Msun) Atlas3D sample of 260 early-type galaxies. We construct detailed axisymmetric dynamical models (JAM), which allow for orbital anisotropy, include a dark matter halo, and reproduce in detail both the galaxy images and the high-quality integral-field stellar kinematics. We derive accurate total M/L and dark matter fractions f_DM, within a sphere of radius r=Re. We also measure the stellar M/L and derive a median dark matter fraction f_DM=13%. We find that the thin two-dimensional subset spanned by galaxies in the (M_JAM,sigma_e,R_e) coordinates system, which we call the Mass Plane (MP) has an observed rms scatter of 19% and an intrinsic one of 11%. The MP satisfies the scalar virial relation M_JAM sigma_e^2 R_e within our tight errors. However, the details of how both Re and sigma_e are determined are critical in defining the precise deviation from the virial exponents. We revisit the (M/L)-sigma_e relation, which describes most of the deviations between the MP and the FP. The best-fitting relation is (M/L) sigma_e^0.72 (r-band). It provides an upper limit to any systematic increase of the IMF mass normalization with sigma_e. We study of the link between sigma_e and the galaxies circular velocity V_circ within 1Re (where stars dominate) and find the relation max(V_circ)~1.76*sigma_e, which has an observed scatter of 7%. The accurate parameters described in this paper are used in the companion Paper XX of this series to explore the variation of global galaxy properties, including the IMF, on the projections of the MP. [Abridged]
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".