ON THE INTERPRETATION OF SUPERNOVA LIGHT ECHO PROFILES AND SPECTRA
Bibliographic record
Abstract
The light echo (LE) systems of historical supernovae in the Milky Way and local group galaxies provide an unprecedented opportunity to reveal the effects of asymmetry on observables, particularly optical spectra. Scattering dust at different locations on the LE ellipsoid witnesses the supernova from different perspectives, and the light consequently scattered toward Earth preserves the shape of line profile variations introduced by asymmetries in the supernova photosphere. However, the interpretation of supernova LE spectra to date has not involved a detailed consideration of the effects of outburst duration and geometrical scattering modifications due to finite scattering dust filament dimension, inclination, and image point-spread function and spectrograph slit width. In this paper, we explore the implications of these factors and present a framework for future-resolved supernova LE spectra interpretation, and test it against Cas A and SN 1987A LE spectra. We conclude that the full modeling of the dimensions and orientation of the scattering dust using the observed LEs at two or more epochs is critical for the correct interpretation of LE spectra. Indeed, without doing so one might falsely conclude that differences exist when none are actually present.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".