Circumstellar Medium Constraints on the Environment of Two Nearby Type Ia Supernovae: SN 2017cbv and SN 2020nlb
Bibliographic record
Abstract
Abstract We present deep Chandra X-ray observations of two nearby Type Ia supernovae, SN 2017cbv and SN 2020nlb, which reveal no X-ray emission down to a luminosity L X ≲ 5.3 × 10 37 and ≲ 5.4 × 10 37 erg s −1 (0.3–10 keV), respectively, at ∼16–18 days after the explosion. With these limits, we constrain the pre-explosion mass-loss rate of the progenitor system to be M ̇ < 7.2 × 10 −9 and < 9.7 × 10 −9 M ⊙ yr −1 for each (at a wind velocity v w = 100 km s −1 and a radius of R ≈ 10 16 cm), assuming any X-ray emission would originate from inverse Compton emission from optical photons upscattered by the supernova shock. If the supernova environment was a constant-density medium, we would find a number density limit of n CSM < 36 and < 65 cm −3 , respectively. These X-ray limits rule out all plausible symbiotic progenitor systems, as well as large swathes of parameter space associated with the single degenerate scenario, such as mass loss at the outer Lagrange point and accretion winds. We also present late-time optical spectroscopy of SN 2020nlb, and set strong limits on any swept up hydrogen ( L H α < 2.7 × 10 37 erg s −1 ) and helium ( L He, λ 6678 < 2.7 × 10 37 erg s −1 ) from a nondegenerate companion, corresponding to M H ≲ 0.7–2 × 10 −3 M ⊙ and M He ≲ 4 × 10 −3 M ⊙ . Radio observations of SN 2020nlb at 14.6 days after explosion also yield a non-detection, ruling out most plausible symbiotic progenitor systems. While we have doubled the sample of normal Type Ia supernovae with deep X-ray limits, more observations are needed to sample the full range of luminosities and subtypes of these explosions, and set statistical constraints on their circumbinary environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".