Fossil group origins V. The dependence of the luminosity function on the magnitude gap
Bibliographic record
Abstract
In nature we observe galaxy aggregations that span a wide range of magnitude gaps between the two first-ranked galaxies of a system ($Δm_{12}$). There are systems with gaps close to zero (e.g., the Coma cluster), and at the other extreme of the distribution, the largest gaps are found among the so-called fossil systems. Fossil and non-fossil systems could have different galaxy populations that should be reflected in their luminosity functions. In this work we study, for the first time, the dependence of the luminosity function parameters on $Δm_{12}$ using data obtained by the fossil group origins (FOGO) project. We constructed a hybrid luminosity function for 102 groups and clusters at $z \le 0.25$. We stacked all the individual luminosity functions, dividing them into bins of $Δm_{12}$, and studied their best-fit Schechter parameters. We additionally computed a relative luminosity function, expressed as a function of the central galaxy luminosity, which boosts our capacity to detect differences, especially at the bright end. We find trends as a function of $Δm_{12}$ at both the bright and faint ends of the luminosity function. In particular, at the bright end, the larger the magnitude gap, the fainter the characteristic magnitude $M^\ast$. We also find differences at the faint end. In this region, the larger the gap, the flatter the faint-end slope $α$. The differences found at the bright end support a dissipationless, dynamical friction-driven merging model for the growth of the central galaxy in group- and cluster-sized halos. The differences in the faint end cannot be explained by this mechanism. Other processes, such as enhanced tidal disruption due to early infall and/or prevalence of eccentric orbits, may play a role. However, a larger sample of systems with $Δm_{12} > 1.5$ is needed to establish the differences at the faint end.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".