TONE: A CHIME/FRB Outrigger Pathfinder for Localizations of Fast Radio Bursts using Very Long Baseline Interferometry
Bibliographic record
Abstract
The sensitivity and field of view of the Canadian Hydrogen Intensity Mapping Experiment (CHIME) has enabled its fast radio burst (FRB) backend to detect thousands of FRBs. However, the low angular resolution of CHIME prevents it from localizing most FRBs to their host galaxies. Very long baseline interferometry (VLBI) can readily provide the subarcsecond resolution needed to localize many FRBs to their hosts. Thus, we developed TONE: an interferometric array of eight 6-m dishes to serve as a pathfinder for the CHIME/FRB Outriggers project, which will use wide field-of-view cylinders to determine the sky positions for a large sample of FRBs, revealing their positions within their host galaxies to subarcsecond precision. In the meantime, TONE’s [Formula: see text] [Formula: see text]km baseline with CHIME proves to be an excellent testbed for the development and characterization of single-pulse VLBI techniques at the time of discovery. This work describes the TONE instrument, its sensitivity, and its astrometric precision in single-pulse VLBI. We believe that our astrometric errors are dominated by uncertainties in the clock measurements which build up between successive Crab pulsar calibrations which happen every [Formula: see text] [Formula: see text]h; the wider fields-of-view and higher sensitivity of the Outriggers will provide opportunities for higher-cadence calibration. At present, CHIME-TONE localizations of the Crab pulsar yield systematic one-dimensional localization errors of [Formula: see text] [Formula: see text]asec — considerably better than the resolution achievable with seeing limited followup observations in the optical/near-infrared from the ground.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".