The dust content of the Crab Nebula
Bibliographic record
Abstract
ABSTRACT We have modelled the near-infrared to radio images of the Crab Nebula with a Bayesian SED model to simultaneously fit its synchrotron, interstellar (IS), and supernova dust emission. We infer an IS dust extinction map with an average AV = 1.08 ± 0.38 mag, consistent with a small contribution (${\lesssim }22{{\ \rm per\ cent}}$) to the Crab’s overall infrared emission. The Crab’s supernova dust mass is estimated to be between 0.032 and 0.049 M⊙ (for amorphous carbon grains) with an average dust temperature Tdust = 41 ± 3 K, corresponding to a dust condensation efficiency of 8–12 ${{\ \rm per\ cent}}$. This revised dust mass is up to an order of magnitude lower than some previous estimates, which can be attributed to our different IS dust corrections, lower SPIRE flux densities, and higher dust temperatures than were used in previous studies. The dust within the Crab is predominantly found in dense filaments south of the pulsar, with an average V-band dust extinction of AV = 0.20–0.39 mag, consistent with recent optical dust extinction studies. The modelled synchrotron power-law spectrum is consistent with a radio spectral index αradio = 0.297 ± 0.009 and an infrared spectral index αIR = 0.429 ± 0.021. We have identified a millimetre excess emission in the Crab’s central regions, and argue that it most likely results from two distinct populations of synchrotron emitting particles. We conclude that the Crab’s efficient dust condensation (8–12 ${{\ \rm per\ cent}}$) provides further evidence for a scenario where supernovae can provide substantial contributions to the IS dust budgets in galaxies.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".