Light curves of type Ia supernovae from near the time of explosion
Bibliographic record
Abstract
We present a set of 11 Type Ia supernova (SN Ia) light curves with dense, premaximum sampling. These supernovae (SNe), in galaxies behind the Large Magellanic Cloud (LMC), were discovered by the SuperMACHO survey. The SNe span a redshift range of z = 0.11 - 0.35. Our light curves contain some of the earliest premaximum observations of SNe Ia to date. We also give a functional model that describes the SN Ia light-curve shape (in our VR band). Our function uses the "expanding fireball" model of Goldhaber et al. to describe the rising light curve immediately after explosion but constrains it to smoothly join the remainder of the light curve. We fit this model to a composite observed VR-band light curve of three SNe between redshifts of 0.135 and 0.165. These SNe have not been K-corrected or adjusted to account for reddening. In this redshift range, the observed VR band most closely matches the rest-frame V band. Using the best fit to our functional description of the light curve, we find the time between explosion and observed VR-band maximum to be 17.6 +/- 1.3(stat) +/- 0.07(sys) rest-frame days for a SN Ia with a VR-band Delta m(-10) of 0.52 mag. For the redshifts sampled, the observed VR-band time of maximum brightness should be the same as the rest-frame V-band maximum to within 1.1 rest-frame days.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".