INTRACLUSTER SUPERNOVAE IN THE MULTI-EPOCH NEARBY CLUSTER SURVEY
Bibliographic record
Abstract
The Multi-Epoch Nearby Cluster Survey has discovered 23 cluster Type Ia supernovae (SNe Ia) in the 58 X-ray-selected galaxy clusters (0.05 ≲ z ≲ 0.15) surveyed. Four of our SN Ia events have no host galaxy on close inspection, and are likely intracluster SNe. Although one of the candidates, Abell399_3_14_0, appears to be associated in projection with the outskirts of a nearby red sequence galaxy, its velocity offset of ∼1000 km s −1 indicates that it is unbound and therefore an intracluster SN. Another of our candidates, Abell85_6_08_0, has a spectrum consistent with an SN1991bg-like object, suggesting that at least some portion of intracluster stars belong to an old stellar population. Deep image stacks at the location of the candidate intracluster SNe put upper limits on the luminosities of faint hosts, with M r ≳ −13.0 mag and M g ≳ −12.5 mag in all cases. For such limits, the fraction of the cluster luminosity in faint dwarfs below our detection limit is ≲0.1%, assuming a standard cluster luminosity function. All four events occurred within ∼600 kpc of the cluster center (projected), as defined by the position of the brightest cluster galaxy, and are more centrally concentrated than the cluster SN Ia population as a whole. After accounting for several observational biases that make intracluster SNe easier to discover and spectroscopically confirm, we calculate an intracluster stellar mass fraction of 0.16 +0.13 −0.09 (68% confidence limit) for all objects within R 200 . If we assume that the intracluster stellar population is exclusively old, and the cluster galaxies themselves have a mix of stellar ages, we derive an upper limit on the intracluster stellar mass fraction of <0.47 (84% one-sided confidence limit). When combined with the intragroup SNe results of McGee & Balogh, we confirm the declining intracluster stellar mass fraction as a function of halo mass reported by Gonzalez and collaborators.
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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 | 0.002 |
| 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 | 0.000 | 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".