Discovery of 20 UV-emitting SNRs in M31 with UVIT
Bibliographic record
Abstract
Abstract We present the first catalog of supernova remnants (SNRs) in M31 that exhibit diffuse ultraviolet (UV) emission. UV images of M31 were obtained by the Ultraviolet Imaging Telescope (UVIT) on the AstroSat satellite, and the list of SNRs was obtained from X-ray, optical, and radio catalogs of SNRs in M31. We used the UVIT images to find SNRs with diffuse emission, omitting those too contaminated with stellar emission. A total of 20 SNRs in M31 were detected with diffuse UV emission. Fluxes in the UVIT F148W, F169M, F172M, N219M, and N279N filters are measured for these SNRs. The luminosities are compared to those computed from the spectra of seven known UV-emitting SNRs in the Milky Way, the Large Magellanic Cloud, and the Small Magellanic Cloud. We find similar spectral shapes between the known and the M31 UV-emitting SNRs. The spectral shapes and the diffuse nature of the emission are good evidence that the UV emissions are dominated by line emissions, like known SNRs, and the UV is associated with the SNRs. Models are applied to the six SNRs with X-ray spectra. The main difference is that the two X-ray/UV SNRs are Type Ia and the four X-ray/non-UV SNRs are core-collapse or unknown type. A comparison of M31 SNRs in different wave bands shows that most are detected optically, similar to the case for other nearby galaxies. A total of 19 of the 20 UV-emitting SNRs are detected optically, expected because both UV and optical are from forbidden and recombination lines from shock-ionized gas.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".