Searching for Historical Extragalactic Optical Transients Associated with Fast Radio Bursts
Bibliographic record
Abstract
Abstract We present a systematic search for past supernovae (SNe) and other historical optical transients at the positions of fast radio burst (FRB) sources to test FRB progenitor systems. Our sample comprises 83 FRBs detected by the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and its k’niʔatn k’l ⌣ stk’masqt Outrigger, along with 93 literature FRBs representing all known well-localized FRBs. We search for optical transients coincident in position and redshift with FRBs and find no significant associations within the 5 σ FRB localization uncertainties except for a previously identified potential optical counterpart to FRB 20180916B. By constraining the timescale for SN ejecta to become transparent to FRB emission, we predict that it takes at least 6–10 yr before the FRB emission can escape. From this, we infer that ≈7% of matched optical transients, up to 30% of currently known SNe, and up to 40% of core-collapse SNe could have an observable FRB based on timescales alone. We derive the number of new, well-localized FRBs required to produce one FRB-SN match by chance, and find it will take ∼22,700 FRBs to yield one chance association at the projected CHIME/FRB Outrigger detection rate. Looking forward, we demonstrate redshift overlap between SNe detected by the upcoming Vera C. Rubin Observatory and CHIME/FRB Outrigger FRBs, indicating the prospect of an increase in potential associations at redshift z < 1. Our framework is publicly available, flexible to a wide range of transient timescales and FRB localization sizes, and can be applied to any optical transient populations in future searches.
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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 | 0.003 | 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) | 0.002 | 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".