A SEARCH FOR FAST RADIO BURSTS AT LOW FREQUENCIES WITH MURCHISON WIDEFIELD ARRAY HIGH TIME RESOLUTION IMAGING
Bibliographic record
Abstract
We present the results of a pilot study search for fast radio bursts (FRBs) using the Murchison Widefield Array (MWA) at low frequencies (139–170 MHz). We utilized MWA data obtained in a routine imaging mode from observations where the primary target was a field being studied for Epoch of Reionization detection. We formed images with 2 s time resolution and 1.28 MHz frequency resolution for 10.5 hr of observations, over 400 square degrees of the sky. We de-dispersed the dynamic spectrum in each of 372,100 resolution elements of 2 × 2 arcmin 2 , between dispersion measures of 170 and 675 pc cm −3 . Based on the event rate calculations in Trott et al., which assume a standard candle luminosity of 8 × 10 37 Js −1 , we predict that with this choice of observational parameters, the MWA should detect (∼10, ∼2, ∼0) FRBs with spectral indices corresponding to (−2, −1, 0), based on a 7 σ detection threshold. We find no FRB candidates above this threshold from our search, placing an event rate limit of above 700 Jy ms per day per sky and providing evidence against spectral indices ( ). We compare our event rate and spectral index limits with others from the literature. We briefly discuss these limits in light of recent suggestions that supergiant pulses from young neutron stars could explain FRBs. We find that such supergiant pulses would have to have much flatter spectra between 150 and 1400 MHz than have been observed from Crab giant pulses to be consistent with the FRB spectral index limit we derive.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".