CHIME/FRB Outriggers: KKO Station System and Commissioning Results
Bibliographic record
Abstract
Abstract Localizing fast radio bursts (FRBs) to their host galaxies is an essential step to better understanding their origins and using them as cosmic probes. The Canadian Hydrogen Intensity Mapping Experiment (CHIME)/FRB Outriggers program aims to add very long baseline interferometry localization capabilities to CHIME, such that FRBs may be localized to tens of milliarcsecond precision at the time of their discovery, more than sufficient for host galaxy identification. The first-built outrigger telescope is the Outrigger (KKO), located 66 km west of CHIME. Cross-correlating KKO with CHIME can achieve arcsecond precision along the baseline axis while avoiding the worst effects of the ionosphere. Since the CHIME–KKO baseline is mostly east/west, this improvement is mostly in right ascension. This paper presents measurements of KKO’s performance throughout its commissioning phase, as well as a summary of its design and function. We demonstrate KKO’s capabilities as a standalone instrument by producing full-sky images, mapping the angular and frequency structure of the primary beam, and measuring feed positions. To demonstrate the localization capabilities of the CHIME–KKO baseline, we collected five separate observations each, for a set of 20 bright pulsars, and aimed to measure their positions to within 5″. All of these pulses were successfully localized to within this specification. The next two outriggers are expected to be commissioned in 2024 and will enable subarcsecond localizations for approximately hundreds of FRBs each year.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".