A Catalog of Local Universe Fast Radio Bursts from CHIME/FRB and the KKO
Bibliographic record
Abstract
Abstract We present the first catalog of fast radio burst (FRB) host galaxies from CHIME/FRB Outriggers, selected uniformly in the radio and the optical by localizing 81 new bursts to 2″ × ∼ 60″ accuracy using CHIME and the k’niʔatn k’l ⌣ stk’masqt Outrigger station, located 66 km from CHIME. Of the 81 localized bursts, we use the probabilistic association of transients to their hosts algorithm to securely identify 21 new FRB host galaxies, and compile spectroscopic redshifts for 19 systems, 15 of which are newly obtained via spectroscopic observations. The most nearby source is FRB 20231229A, at a distance of 90 Mpc. One burst in our sample is from a previously reported repeating source in a galaxy merger (FRB 20190303A). Three new FRB host galaxies (FRBs 20230203A, 20230703A, and 20231206A) are found toward X-ray and optically selected galaxy clusters, potentially doubling the sample of known galaxy cluster FRBs. A search for radio counterparts reveals that FRB 20231128A is associated with a luminous persistent radio source (PRS) candidate with high significance ( P cc ∼ 10 −2 ). If its compactness is confirmed, it would be the nearest known compact PRS at z = 0.1079. Our catalog significantly increases the statistics of the Macquart relation at low redshifts ( z < 0.2). In the near future, the completed CHIME/FRB Outriggers array will produce hundreds of FRBs localized with very long baseline interferometry (VLBI). This will significantly expand the known sample and pave the way for future telescopes relying on VLBI for FRB localization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".