Core-collapse supernova subtypes in luminous infrared galaxies
Bibliographic record
Abstract
The fraction of core-collapse supernovae (CCSNe) occurring in the central regions of galaxies is not well constrained at present. This is partly because large-scale transient surveys operate at optical wavelengths, making it challenging to detect transient sources that occur in regions susceptible to high extinction factors. Here we present the discovery and follow-up observations of two CCSNe that occurred in the luminous infrared galaxy (LIRG) NGC 3256. The first, SN 2018ec, was discovered using the ESO HAWK-I/GRAAL adaptive optics seeing enhancer, and was classified as a Type Ic with a host galaxy extinction of A V = 2.1 −0.1 +0.3 mag. The second, AT 2018cux, was discovered during the course of follow-up observations of SN 2018ec, and is consistent with a subluminous Type IIP classification with an A V = 2.1 ± 0.4 mag of host extinction. A third CCSN, PSN J10275082−4354034 in NGC 3256, was previously reported in 2014, and we recovered the source in late-time archival Hubble Space Telescope imaging. Based on template light curve fitting, we favour a Type IIn classification for it with modest host galaxy extinction of A V = 0.3 −0.3 +0.4 mag. We also extend our study with follow-up data of the recent Type IIb SN 2019lqo and Type Ib SN 2020fkb that occurred in the LIRG system Arp 299 with host extinctions of A V = 2.1 −0.3 +0.1 and A V = 0.4 −0.2 +0.1 mag, respectively. Motivated by the above, we inspected, for the first time, a sample of 29 CCSNe located within a projected distance of 2.5 kpc from the host galaxy nuclei in a sample of 16 LIRGs. We find, if star formation within these galaxies is modelled assuming a global starburst episode and normal IMF, that there is evidence of a correlation between the starburst age and the CCSN subtype. We infer that the two subgroups of 14 H-poor (Type IIb/Ib/Ic/Ibn) and 15 H-rich (Type II/IIn) CCSNe have different underlying progenitor age distributions, with the H-poor progenitors being younger at 3 σ significance. However, we note that the currently available sample sizes of CCSNe and host LIRGs are small, and the statistical comparisons between subgroups do not take into account possible systematic or model errors related to the estimated starburst ages.
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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) | 0.001 | 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".