Measurement of the Rate Distribution of the Population of Repeating Fast Radio Bursts: Implications for Progenitor Models
Bibliographic record
Abstract
Abstract The discovery of many repeating fast radio bursts (FRBs) by the Canadian Hydrogen Intensity Mapping Experiment, the high rate of individual bursts, and the observation of repeat bursts from a bright FRB initially detected by the Australian Square Kilometre Array Pathfinder (ASKAP) suggest a significant population of repeating FRBs. Here, we analyze the rate distribution of this population using results from follow-up observations of the Commensal Real-time ASKAP Fast Transients Survey. Characterizing a repeating FRB by its burst rate R 0 above an energy of 1038 erg, we consider a volumetric density Φ(R 0) with rate distribution <?CDATA $d{\rm{\Phi }}\propto {R}_{0}^{\zeta }{{dR}}_{0}$?> . We use maximum-likelihood methods to constrain ζ < −1.94 at 90% confidence. We discuss how this constraint can be used to limit different classes of progenitor models for repeating FRBs: it excludes FRBs with burst rate proportional to neutron star spin-down power with braking index n ≤ 14, i.e., magnetic dipole radiation (n = 3); and it excludes some scenarios for FRB emission from magnetars, and the magnetic field interactions of compact binaries.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".