Galaxy–halo size relation from Sloan Digital Sky Survey Data Release 7 and the ELUCID simulation
Bibliographic record
Abstract
ABSTRACT Based on galaxies in the Sloan Digital Sky Survey Data Release 7 and dark matter haloes in the dark matter only, cosmological, and constrained ELUCID simulation, we investigate the relation between the observed radii of central galaxies with stellar mass $\gtrsim\!{10}^{8} \, h^{-2}\, {\rm M}_\odot$ and the virial radii of their host dark matter haloes with virial mass $\gtrsim\!{10}^{10.5} \, h^{-1}\, {\rm M}_\odot$, and the dependence of galaxy–halo size relation on the halo spin and concentration. Galaxies in observation are matched to dark matter (sub)haloes in the ELUCID simulation using a novel neighbourhood subhalo abundance matching method. For galaxy two-dimensional (2D) half-light radii R50, we find that early- and late-type galaxies have the same power-law index 0.55 with $R_{50} \propto R_{\rm vir}^{0.55}$, although early-type galaxies have smaller 2D half-light radii than late-type galaxies at fixed halo virial radii. When converting the 2D half-light radii R50 to 3D half-mass radii r1/2, both early- and late-type galaxies display similar galaxy–halo size relations with $\log r_{1/2} = 0.55 \log (R_{\rm vir}/210 \, h^{-1}\, {\rm kpc}) + 0.39$. We find that the galaxy–halo size ratio r1/2/Rvir decreases with increasing halo mass. At fixed halo mass, there is no significant dependence of galaxy–halo size ratio on the halo spin or concentration.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".