The deepest<i>Chandra</i>X-ray study of the plerionic supernova remnant G21.5−0.9
Bibliographic record
Abstract
G21.5-0.9 is a plerionic supernova remnant (SNR) used as a calibration target for the Chandra X-ray telescope. The first observations found an extended halo surrounding the bright central pulsar wind nebula (PWN). A 2005 study discovered that this halo is limb-brightened and suggested the halo to be the missing SNR shell. In 2010 the spectrum of the limb-brightened shell was found to be dominated by non-thermal X-rays. In this study, we combine 15 years of Chandra observations comprising over 1~Msec of exposure time (796.1~ks with the Advanced CCD Imaging Spectrometer (ACIS) and 306.1~ks with the High Resolution Camera (HRC)) to provide the deepest-to-date imaging and spectroscopic study. The emission from the limb is primarily non-thermal and is described by a power-law model with a photon index $\Gamma = 2.22 \, (2.04-2.34)$, plus a weak thermal component characterized by a temperature $kT = 0.37\, (0.20-0.64)$ keV and a low ionization timescale of $n_{e}t < 2.95 \times 10^{10}$ cm$^{-3}$s. The northern knot located in the halo is best fitted with a two-component power-law + non-equilibrium ionization thermal model characterized by a temperature of 0.14 keV and an enhanced abundance of silicon, confirming its nature as ejecta. We revisit the spatially resolved spectral study of the PWN and find that its radial spectral profile can be explained by diffusion models. The best fit diffusion coefficient is $D \sim 2.1\times 10^{27}\rm cm^2/s$ assuming a magnetic field $B =130 \mu G$, which is consistent with recent 3D MHD simulation results.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".