Discovery of Perun (G329.9−0.5): a new, young, Galactic SNR
Bibliographic record
Abstract
ABSTRACT We present the discovery of possibly the youngest Galactic supernova remnant (SNR) with associated pulsar-wind nebula (PWN), which we name Perun (G329.9−0.5). Perun was serendipitously discovered in the Australian Square Kilometre Array Pathfinder–Evolutionary Map of the Universe survey at 943 MHz, and subsequent follow-up observations were conducted with the Australia Telescope Compact Array observatory at 5500 and 9000 MHz. We combine these with additional radio observations from the MeerKAT, Molonglo Observatory Synthesis Telescope, and Murchison Widefield Array telescopes, infrared (IR) observations from the SpitzerSpace Telescope, and X-ray observations from the Chandra X-ray observatory to perform a multifrequency analysis. The radio morphology shows a small angular size shell (D = 70 arcsec) with a luminous, central PWN. We measure a total spectral index of $\alpha = -0.49\pm 0.05$, which should be typical for a young, composite SNR. Crucial evidence for Perun’s SNR classification comes from the detection of linear fractional polarization at radio frequencies of $\sim$7 per cent–10 per cent with both radial and tangential orientations, similar to the young SNR G1.9+0.3. We use data from the Southern Galactic Plane Survey to perform an H i analysis and estimate a favoured distance range of 6–9 kpc, and thus a favoured age range of $\sim$70–500 yr. We find no high-energy emission in Fermi-Large Area Telescope data. We detect Perun’s outer shell in 24 $\mu$m indicating the possible presence of [O iv] and [Fe iii] emission, also typical for young SNRs. Overall, these observations and analysis confirm Perun as a young, Galactic SNR with a prominent PWN.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".