Early Color Photometry of the Type Iax Supernova 2023mnc: Inferring the Distance and Progenitor Constraints
Bibliographic record
Abstract
Abstract Early-time radioactive signals from type Ia supernovae (SNeIa) can provide important constraints on the explosion mechanism and the progenitor system. We present observations and analysis of SN2023mnc, a SN Ia, ∼ 7 days following its discovery. Follow-up observations were conducted in opticalbands, covering phases from ∼ −4 days to ∼ 15 days relative to its g-band peak luminosity. The early photometry allows us to estimate the physical properties of the ejecta and characterize the possible divergence from a normal SN Ia; we were able to characterize it as a Type Iax supernova instead. The estimated date of explosion is t0 = 60130 MJD and implies a short rise time of trise ≈ 16 days. The apparent g-band peak magnitude and the post-peak decline rate are mmax(g) = −19.52 ± 0.47mag and ∆m15(g) = −0.825 ± 1.635 mag, respectively. Based on the light curve fitting of standard SN Ia models, the distance modulus is predicted to be 37.98 ± 0.207 mag for g band measurements, and the SN is predicted to be 394.46 ± 38 Mpc from Earth. Assuming a 56Ni powered radiativediffusion, the estimated bolometric light-curve peaks at 1.08ergs−1 and indicates that only 0.05M⊙ of 56Ni was produced, making SN 2023mnc a moderate luminosity object in the Iax class with peak absolute magnitude of MV = −16.4 mag. Comparing the observed color evolution with the predictedby different models such as deflagration-to-detonation transition and pure-deflagration scenario, the latter one is favored. The photometry of SN 2023mnc offers a unique opportunity to examine the progenitor systems and ignition process of the SNe Iax, adding weight to the population study of such sub-class SNe.
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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".