The Dispersion and Rotation Measure of Supernova Remnants and Magnetized Stellar Winds: Application to Fast Radio Bursts
Bibliographic record
Abstract
Abstract Recent studies of fast radio bursts (FRBs) have led to many theories associating them with young neutron stars. If this is the case, then the presence of supernova ejecta and stellar winds provides a changing dispersion measure (DM) and rotation measure (RM) that can potentially be probes of the environments of FRB progenitors. Here we summarize the scalings for the DM and RM in the cases of a constant density ambient medium and of a progenitor stellar wind. Since the amount of ionized material is controlled by the dynamics of the reverse shock, we find that the DM changes more slowly than in previous simpler work, which assumed a constant ionization fraction. Furthermore, the DM can be constant or even increasing as the supernova remnant sweeps up material, arguing that a young neutron star hypothesis for FRBs is not ruled out if the DM is not decreasing over repeated bursts. The combined DM and RM measurements for the repeating FRB 121102 are consistent with supernova ejecta with an age of ∼10 2 –10 3 years expanding into a high density (∼100 cm −3 ) interstellar medium. This naturally explains its relatively constant DM over many years as well. Other FRBs with much lower RMs may indicate that they are especially young supernovae in wind environments or that their DMs are largely from the intergalactic medium. We therefore caution about inferring magnetic fields simply by dividing an RM by DM, because these quantities could originate from distinct regions along the path an FRB propagates.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".