MERGERS IN GALAXY GROUPS. II. THE FUNDAMENTAL PLANE OF ELLIPTICAL GALAXIES
Bibliographic record
Abstract
Observations consistently show that elliptical galaxies follow a tight "fundamental plane" (FP) scaling relation between size, mean surface brightness, and velocity dispersion, with the form . This relation not only has very small (<0.05 dex) intrinsic scatter, but also has significantly different coefficients from the expected virial scaling (a "tilt"). We analyze hundreds of simulations of elliptical galaxies formed from mergers of spiral galaxies in groups to determine if the FP can emerge from multiple, mostly minor and hierarchical collisionless mergers. We find that these simulated ellipticals lie on a similar FP with and . The scatter about this plane is not larger than observed, while the tilt is in the correct sense, although a is larger than for typical observations. This supports the idea that collisionless mergers can contribute significantly to the tilt of the FP. The tilt is mainly driven by a mass-dependent dark matter fraction, such that more massive galaxies have larger dark matter fractions within R e . We further discuss the origin of this mass-dependent dark matter fraction and its compatibility with strong lensing observations, as well as the links between the FP, dynamical masses, and the virial theorem.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".