The Occurrence of Compact Groups of Galaxies through Cosmic Time
Bibliographic record
Abstract
Abstract We use the outputs of a semianalytical model of galaxy formation run on the Millennium Simulation to investigate the prevalence of 3D compact groups (CGs) of galaxies from z = 11 to 0. Our publicly available code identifies CGs using the 3D galaxy number density, the mass ratio of secondary+tertiary to the primary member, mass density in a surrounding shell, the relative velocities of candidate CG members, and a minimum CG membership of three. We adopt “default” values for the first three criteria, representing the observed population of Hickson CGs at z = 0. The percentage of nondwarf galaxies (M > 5 × 108 h −1 M ⊙) in CGs peaks near z ∼ 2 for the default set and in the range of z ∼ 1–3 for other parameter sets. This percentage declines rapidly at higher redshifts (z ≳ 4), consistent with the galaxy population as a whole being dominated by low-mass galaxies excluded from this analysis. According to the most liberal criteria, ≲3% of nondwarf galaxies are members of CGs at the redshift where the CG population peaks. Our default criteria result in a population of CGs at z < 0.03 with number densities and sizes consistent with Hickson CGs. Tracking identified CG galaxies and merger products to z = 0, we find that ≲16% of nondwarf galaxies have been CG members at some point in their history. Intriguingly, the great majority (96%) of z = 2 CGs have merged to a single galaxy by z = 0. There is a discrepancy in the velocity dispersions of Millennium Simulation CGs compared to those in observed CGs, which remains unresolved.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".