SN 2023ixf in the Pinwheel Galaxy M101: From Shock Breakout to the Nebular Phase
Bibliographic record
Abstract
Abstract We present photometric and spectroscopic observations of supernova SN 2023ixf covering from day 1 to 442 days after explosion. SN 2023ixf reached a peak V -band absolute magnitude of −18.2 ± 0.07, and light curves show that it has a relatively short “plateau” phase (∼72 days), and can be classified either as an SN IIL or a transitional event between IIP and IIL. Early-time spectra of SN 2023ixf exhibit strong, very narrow emission lines from ionized circumstellar matter (CSM), possibly indicating a Type IIn classification. But these flash/shock-ionization emission features faded after the first week and the spectrum evolved in a manner similar to that of typical Type II SNe, unlike the case of most genuine SNe IIn in which the ejecta interact with CSM for an extended period of time and develop intermediate-width emission lines. We compare observed spectra of SN 2023ixf with various model spectra to understand the physics behind SN 2023ixf. Our nebular spectra (between 200 and 400 days) match best with the model spectra from a 15 M ⊙ progenitor that experienced enhanced mass loss a few years before explosion. A last-stage mass-loss rate of M ̇ = 0.01 M ⊙ yr − 1 from the r1w6 model matches best with the early-time spectra, higher than M ̇ ≈ 2.4 × 1 0 − 3 M ⊙ yr − 1 derived from the ionized H α luminosity at 1.58 days. We also use SN 2023ixf as a distance indicator and fit the light curves to derive the Hubble constant by adding SN 2023ixf to the existing sample; we obtain H 0 = 73 . 1 − 3.50 + 3.68 km s −1 Mpc −1 , consistent with the results from SNe Ia and many other independent methods.
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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".