Morphology of 35 Repeating Fast Radio Burst Sources at Microsecond Time Scales with CHIME/FRB
Bibliographic record
Abstract
Abstract The Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) project has discovered the most repeating FRB sources of any telescope. However, most of the physical conclusions derived from this sample are based on data with a time resolution of ∼1 ms. In this work, we present for the first time a morphological analysis of the raw voltage data for 124 bursts from 35 of CHIME/FRB's repeating sources. We do not find any significant correlations among fluence, dispersion measure (DM), burst rate, and burst duration. Performing the first large-scale morphological comparison at timescales down to microseconds between our repeating sources and 125 nonrepeating FRBs, we find that repeaters are narrower in frequency and broader in duration than nonrepeaters, supporting previous findings. However, we find that the duration-normalized sub-burst widths of the two populations are consistent, possibly suggesting a shared physical emission mechanism. Additionally, we find that the spectral fluences of the two are consistent. When combined with the larger bandwidths and previously found larger DMs of nonrepeaters, this suggests that nonrepeaters may have higher intrinsic specific energies than repeating FRBs. We do not find any consistent increase or decrease in the DM (⪅1 pc cm −3 yr −1 ) and scattering timescales (⪅2 ms yr −1 ) of our sources over ∼2–4 yr periods.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".