Weak Mass Loss from the Red Supergiant Progenitor of the Type II SN 2021yja
Bibliographic record
Abstract
Abstract We present high-cadence optical, ultraviolet (UV), and near-infrared data of the nearby ( D ≈ 23 Mpc) Type II supernova (SN) 2021yja. Many Type II SNe show signs of interaction with circumstellar material (CSM) during the first few days after explosion, implying that their red supergiant (RSG) progenitors experience episodic or eruptive mass loss. However, because it is difficult to discover SNe early, the diversity of CSM configurations in RSGs has not been fully mapped. SN 2021yja, first detected within ≈ 5.4 hours of explosion, shows some signatures of CSM interaction (high UV luminosity and radio and x-ray emission) but without the narrow emission lines or early light-curve peak that can accompany CSM. Here we analyze the densely sampled early light curve and spectral series of this nearby SN to infer the properties of its progenitor and CSM. We find that the most likely progenitor was an RSG with an extended envelope, encompassed by low-density CSM. We also present archival Hubble Space Telescope imaging of the host galaxy of SN 2021yja, which allows us to place a stringent upper limit of ≲ 9 M ☉ on the progenitor mass. However, this is in tension with some aspects of the SN evolution, which point to a more massive progenitor. Our analysis highlights the need to consider progenitor structure when making inferences about CSM properties, and that a comprehensive view of CSM tracers should be made to give a fuller view of the last years of RSG evolution.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".