A cool and inflated progenitor candidate for the Type Ib supernova 2019yvr at 2.6 yr before explosion
Bibliographic record
Abstract
ABSTRACT We present Hubble Space Telescope imaging of a pre-explosion counterpart to SN 2019yvr obtained 2.6 yr before its explosion as a type Ib supernova (SN Ib). Aligning to a post-explosion Gemini-S/GSAOI image, we demonstrate that there is a single source consistent with being the SN 2019yvr progenitor system, the second SN Ib progenitor candidate after iPTF13bvn. We also analysed pre-explosion Spitzer/Infrared Array Camera (IRAC) imaging, but we do not detect any counterparts at the SN location. SN 2019yvr was highly reddened, and comparing its spectra and photometry to those of other, less extinguished SNe Ib we derive $E(B-V)=0.51\substack{+0.27\\ -0.16}$ mag for SN 2019yvr. Correcting photometry of the pre-explosion source for dust reddening, we determine that this source is consistent with a log (L/L⊙) = 5.3 ± 0.2 and $T_{\mathrm{eff}} = 6800\substack{+400\\ -200}$ K star. This relatively cool photospheric temperature implies a radius of 320$\substack{+30\\ -50}~\mathrm{ R}_{\odot}$, much larger than expectations for SN Ib progenitor stars with trace amounts of hydrogen but in agreement with previously identified SN IIb progenitor systems. The photometry of the system is also consistent with binary star models that undergo common envelope evolution, leading to a primary star hydrogen envelope mass that is mostly depleted but still seemingly in conflict with the SN Ib classification of SN 2019yvr. SN 2019yvr had signatures of strong circumstellar interaction in late-time (>150 d) spectra and imaging, and so we consider eruptive mass-loss and common envelope evolution scenarios that explain the SN Ib spectroscopic class, pre-explosion counterpart, and dense circumstellar material. We also hypothesize that the apparent inflation could be caused by a quasi-photosphere formed in an extended, low-density envelope, or circumstellar matter around the primary star.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".