A UNIONS view of the brightest central galaxies of candidate fossil groups
Bibliographic record
Abstract
Context. The formation process of fossil groups (FGs) is still under debate, and, because of their relative rarity, large samples of such objects are still missing. Aims. The aim of the present paper is to increase the sample of known FGs, to analyse the properties of their brightest group galaxies (BGGs), and to compare them with a control sample of non-FG BGGs. Methods. We extracted a sample of 87 FG and 100 non-FG candidates from a large spectroscopic catalogue of haloes and galaxies. For all the objects with data available in UNIONS (initially the Canada France Imaging Survey, CFIS) in the u and r bands, and/or in an extra r-band processed to preserve all low-surface-brightness features (rLSB), we performed a 2D photometric fit of the BGG with GALFIT with one or two Sérsic components. We also analysed how the subtraction of the intracluster light (ICL) contribution modifies the BGG properties. From the SDSS spectra available for the BGGs of 65 FGs and 82 non-FGs, we extracted the properties of their stellar populations with Firefly. To complement our study, and in order to provide a detailed illustration of the possible origin of emission lines in the FG BGGs, involving the presence or absence of an AGN, we investigated the origin of the emission lines in a nearby FG that is dominated by the NGC 4104 galaxy. Results. Morphologically, a single Sérsic profile can fit most objects in the u band, while two Sérsics are needed in the r and rLSB bands, both for FGs and non-FGs. Non-FG BGGs cover a larger range of Sérsic index n. FG BGGs follow the Kormendy relation (mean surface brightness versus effective radius) previously derived for almost 1000 brightest cluster galaxies (BCGs), while the majority of non-FGs BGGs are located below this relation, with fainter mean surface brightnesses. This suggests that FG BGGs have evolved similarly to BCGs, and non-FG BGGs have evolved differently from both FG BGGs and BCGs. All the above properties can be strongly modified by the subtraction of the ICL contribution. Based on spectral fitting, the stellar populations of FG and non-FG BGGs do not differ significantly. Conclusions. FG and non-FG BGGs differ from one another in terms of their morphological properties and Kormendy relation, suggesting they have had different formation histories. However, it is not possible to trace differences in their stellar populations or in their large-scale distributions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".