The Fundamental Plane in the LEGA-C Survey: Unraveling the M/L Ratio Variations of Massive Star-forming and Quiescent Galaxies at z ∼ 0.8
Bibliographic record
Abstract
Abstract We explore the connection between the kinematics, structures and stellar populations of massive galaxies at 0.6 < z < 1.0 using the fundamental plane (FP). Combining stellar kinematic data from the Large Early Galaxy Astrophysics Census (LEGA-C) survey with structural parameters measured from deep Hubble Space Telescope imaging, we obtain a sample of 1419 massive ( log ( M * / M ⊙ ) > 10.5 ) galaxies that span a wide range in morphology, star formation activity, and environment, and therefore is representative of the massive galaxy population at z ∼ 0.8. We find that quiescent and star-forming galaxies occupy the parameter space of the g -band FP differently and thus have different distributions in the dynamical mass-to-light ratio ( M dyn / L g ), largely owing to differences in the stellar age and recent star formation history, and to a lesser extent, the effects of dust attenuation. In contrast, we show that both star-forming and quiescent galaxies lie on the same mass FP at z ∼ 0.8, with a comparable level of intrinsic scatter about the plane. We examine the variation in M dyn / M * through the thickness of the mass FP, finding no significant residual correlations with stellar population properties, Sérsic index, or galaxy overdensity. Our results suggest that, at fixed size and velocity dispersion, the variations in M dyn / L g of massive galaxies reflect an approximately equal contribution of variations in M * / L g , and variations in the dark matter fraction or initial mass function.
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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 | 0.002 | 0.002 |
| 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".