Luminous Radio Emission from the Superluminous Supernova 2017ens at 3.3 yr after Explosion
Bibliographic record
Abstract
Abstract We present the results from a multiyear radio campaign of the superluminous supernova (SLSN) SN 2017ens, which yielded the earliest radio detection of an SLSN to date at the age of ∼3.3 yr after explosion. SN 2017ens was not detected at radio frequencies in the first ∼300 days but reached L ν ≈ 1028 erg s−1 cm−2 Hz−1 at ν ∼ 6 GHz, ∼1250 days post explosion. Interpreting the radio observations in the context of synchrotron radiation from the supernova shock interaction with the circumstellar medium (CSM), we infer an effective mass-loss rate M ̇ ≈ 10 − 4 M ☉ yr − 1 at r ∼ 1017 cm from the explosion’s site, for a wind speed of v w = 50–60 km s−1 as measured from optical spectra. These findings are consistent with the spectroscopic metamorphosis of SN 2017ens from hydrogen poor to hydrogen rich ∼190 days after explosion reported by Chen et al. SN 2017ens is thus an addition to the sample of hydrogen-poor massive progenitors that explode shortly after having lost their hydrogen envelope. The inferred circumstellar densities, implying a CSM mass up to ∼0.5 M ☉, and low velocity of the ejection suggest that binary interactions (in the form of common-envelope evolution and subsequent envelope ejection) play a role in shaping the evolution of the stellar progenitors of SLSNe in the ≲500 yr preceding core collapse.
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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 | 0.000 | 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".