Polarization Properties of 28 Repeating Fast Radio Burst Sources with CHIME/FRB
Bibliographic record
Abstract
Abstract As part of the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) project, we report 41 new rotation measures (RMs) from 20 repeating fast radio bursts (FRBs) obtained between 2019 and 2023 for which no previous RM was determined. We also report 22 additional RM measurements for eight further repeating FRBs. We observe temporal RM variations in practically all repeating FRBs. Repeaters appear to be separated into two categories: those with dynamic and those with stable RM environments, differentiated by the ratios of RM standard deviations to the averaged RM magnitudes. Sources from stable RM environments likely have small RM contributions from the interstellar medium of their host galaxies, whereas sources from dynamic RM environments share some similarities with Galactic pulsars in eclipsing binaries but appear distinct from solitary pulsars in the Galactic centre. We observe a new stochastic, secular, and again stochastic trend in the temporal RM variation of FRB 20180916B, which does not support binary orbit modulation being its cause. We highlight two more repeaters that show RM sign change, namely FRBs 20290929C and 20190303A. We perform an updated comparison of polarization properties between repeating and nonrepeating FRBs, which show a marginal dichotomy in their distribution of electron-density-weighted parallel-component line-of-sight magnetic fields.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".