SUPER-LUMINOUS TYPE Ic SUPERNOVAE: CATCHING A MAGNETAR BY THE TAIL
Bibliographic record
Abstract
We report extensive observational data for five of the lowest redshift Super-Luminous Type Ic Supernovae (SL-SNe Ic) discovered to date, namely, PTF10hgi, SN2011ke, PTF11rks, SN2011kf, and SN2012il. Photometric imaging of the transients at +50 to +230 days after peak combined with host galaxy subtraction reveals a luminous tail phase for four of these SL-SNe. A high-resolution, optical, and near-infrared spectrum from xshooter provides detection of a broad He i λ10830 emission line in the spectrum (+50 days) of SN2012il, revealing that at least some SL-SNe Ic are not completely helium-free. At first sight, the tail luminosity decline rates that we measure are consistent with the radioactive decay of 56 Co, and would require 1–4 M ☉ of 56 Ni to produce the luminosity. These 56 Ni masses cannot be made consistent with the short diffusion times at peak, and indeed are insufficient to power the peak luminosity. We instead favor energy deposition by newborn magnetars as the power source for these objects. A semi-analytical diffusion model with energy input from the spin-down of a magnetar reproduces the extensive light curve data well. The model predictions of ejecta velocities and temperatures which are required are in reasonable agreement with those determined from our observations. We derive magnetar energies of 0.4 ≲ E (10 51 erg) ≲ 6.9 and ejecta masses of 2.3 ≲ M ej ( M ☉ ) ≲ 8.6. The sample of five SL-SNe Ic presented here, combined with SN 2010gx—the best sampled SL-SNe Ic so far—points toward an explosion driven by a magnetar as a viable explanation for all SL-SNe Ic.
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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 | 0.001 |
| 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".