Supernovae and their host galaxies – VII. The diversity of Type Ia supernova progenitors
Bibliographic record
Abstract
ABSTRACT We present an analysis of the light curve (LC) decline rates (Δm15) of 407 normal and peculiar supernovae (SNe) Ia and global parameters of their host galaxies. As previously known, there is a significant correlation between the Δm15 of normal SNe Ia and global ages (morphologies, colours, and masses) of their hosts. On average, those normal SNe Ia that are in galaxies from the Red Sequence (early-type, massive, old hosts) have faster declining LCs in comparison with those from the Blue Cloud (late-type, less massive, younger hosts) of the colour–mass diagram. The observed correlations between the Δm15 of normal SNe Ia and hosts’ parameters appear to be due to the superposition of at least two distinct populations of faster and slower declining normal SNe Ia from older and younger stellar components. We show, for the first time, that the Δm15 of 91bg- and 91T-like SNe is independent of host morphology and colour. The distribution of hosts on the colour–mass diagram confirms the known tendency for 91bg-like SNe to occur in globally red/old galaxies, while 91T-like events prefer blue/younger hosts. On average, the youngest global ages of 02cx-like SNe hosts and their positions in the colour–mass diagram hint that these events likely originate from young population, but they differ from 91T-like events in the LC decline rate. Finally, we discuss the possible explosion channels and present our favoured SN Ia models that have the potential to explain the observed SN–host relations.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".