The story of SN 2021aatd: A peculiar 1987A-like supernova with an early-phase luminosity excess
Bibliographic record
Abstract
Context. There is a growing number of peculiar events that cannot be assigned to any of the main classes. SN 1987A and a handful of similar objects, thought to be explosive outcomes of blue supergiant stars, is one of them: while their spectra closely resemble those of H-rich (IIP) SNe, their light curve (LC) evolution is very different. Aims. Here we present the detailed photometric and spectroscopic analysis of SN 2021aatd, a peculiar Type II explosion. While its early-time evolution resembles that of the slowly evolving double-peaked SN 2020faa (although at a lower luminosity scale), after ∼40 days its LC shape becomes similar to that of SN 1987A-like explosions. Methods. In addition to comparing LCs, color curves, and spectra of SN 2021aatd to those of SNe 2020faa, 1987A, and other objects, we compared the observed spectra with our own SYN++ models and with the outputs of published radiative transfer models. We also carried out a detailed modeling of the pseudo-bolometric LCs of SNe 2021aatd and 1987A with a self-developed semi-analytical code, assuming a two-component ejecta (core + shell), and involving the rotational energy of a newborn magnetar in addition to radioactive decay. Results. We find that the photometric and the spectroscopic evolution of SN 2021aatd can be well described with the explosion of a ∼15 M⊙ blue supergiant star. Nevertheless, SN 2021aatd shows higher temperatures and weaker Na I D and Ba II 6142 Å lines than SN 1987A, which is instead reminiscent of IIP-like atmospheres. With the applied two-component ejecta model (accounting for decay and magnetar energy), we can successfully describe the bolometric LC of SN 2021aatd, including the first ∼40-day phase showing an excess compared to 87A-like SNe, but being strikingly similar to that of the long-lived SN 2020faa. Nevertheless, finding a unified model that also explains the LCs of more luminous events (e.g., SN 2020faa) is still a matter of debate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".