The First Systematic Study of Type Ibc Supernova Multi-band Light Curves
Bibliographic record
Abstract
We present detailed optical photometry for 25 Type Ibc supernovae within d\approx150 Mpc obtained with the robotic Palomar 60-inch telescope in 2004-2007. This study represents the first uniform, systematic, and statistical sample of multi-band SNe Ibc light curves available to date. We correct the light curves for host galaxy extinction using a new technique based on the photometric color evolution, namely, we show that the (V-R) color of extinction-corrected SNe Ibc at t\approx10 days after V-band maximum is tightly distributed, (V-R)=0.26+-0.06 mag. Using this technique, we find that SNe Ibc typically suffer from significant host galaxy extinction, E(B-V)\approx0.4 mag. A comparison of the extinction-corrected light curves for SNe Ib and Ic reveals that they are statistically indistinguishable, both in luminosity and decline rate. We report peak absolute magnitudes of M_R=-17.9+-0.9 mag and M_R=-18.3+-0.6 mag for SNe Ib and Ic, respectively. Focusing on the broad-lined SNe Ic, we find that they are more luminous than the normal SNe Ibc sample, M_R=-19.0+-1.1 mag, with a probability of only 1.6% that they are drawn from the same population of explosions. By comparing the peak absolute magnitudes of SNe Ic-BL with those inferred for local engine-driven explosions (GRB-SN 1998bw, XRF-SN 2006aj, and SN2009bb) we find a 25% probability that they are drawn from the SNe Ic-BL population. Finally, we fit analytic models to the light-curves to derive typical Ni-56 masses of M_Ni \approx0.2 and 0.5 M_sun for SNe Ibc and SNe Ic-BL, respectively. With reasonable assumptions for the photospheric velocities, we extract kinetic energy and ejecta mass values of M_ej \approx 2 M_sun and E_K\approx1e+51 erg for SNe Ibc, while for SNe Ic-BL we find higher values, M_ej\approx5 M_sun and E_K\approx1e+52 erg. We discuss the implications for the progenitors of SNe Ibc and their relation to engine-driven explosions [ABRIDGED].
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".