Evolutionary Models for 43 Galactic Supernova Remnants with Distances and X-Ray Spectra
Bibliographic record
Abstract
Abstract The X-ray emission from a supernova remnant (SNR) is a powerful diagnostic of the state of the shocked plasma. The temperature ( kT ) and the emission measure (EM) of the shocked gas are related to the energy of the explosion, the age of the SNR, and the density of the surrounding medium. Progress in X-ray observations of SNRs has resulted in a significant sample of Galactic SNRs with measured kT and EM values. We apply spherically symmetric SNR evolution models to a new set of 43 SNRs to estimate ages, explosion energies, and circumstellar medium densities. The distribution of ages yields an SNR birth rate. The energies and densities are well fit with lognormal distributions, with wide dispersions. SNRs with two emission components are used to distinguish between SNR models with uniform interstellar medium and with stellar wind environment. We find Type Ia SNRs to be consistent with a stellar wind environment. Inclusion of stellar wind SNR models has a significant effect on estimated lifetimes and explosion energies of SNRs. This reduces the discrepancy between the estimated SNR birth rate and the SN rate of the Galaxy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".