Burst properties of the highly active FRB20201124A using uGMRT
Bibliographic record
Abstract
Abstract We report the observations of the highly active FRB20201124A with the upgraded Giant Metrewave Radio Telescope at 550-750 MHz. These observations in the incoherent array mode simultaneously provided an arcsecond localization of bursts from FRB20201124A, the discovery of persistent radio emission associated with the host galaxy, and the detection of 48 bursts. Using the brightest burst in the sample (F = 108 Jy ms) we find a structure-maximizing dispersion measure of 410.8 ± 0.5 pc cm−3. We find that our observations are complete down to a fluence level of 10 Jy ms, above which the cumulative burst rate scales as a power-law R( > F) = 10 hr−1(F/10 Jy ms)γ with γ = −1.2 ± 0.2. We find that the bursts are on average wider than those reported for other repeating FRBs. We find that the waiting time between bursts is well approximated by an exponential distribution with a mean of ∼2.9 min during our observations. We searched for periodicities using both a standard Fourier domain method and the Fast Folding Algorithm, but found no significant candidates. We measure bulk spectro-temporal drift rates between −0.75 and −20 MHz ms−1. Finally, we use the brightest burst to set an upper limit to the scattering time of 11.1 ms at 550 MHz. The localization of FRB20201124A adds strength to the proof-of-concept method described in our earlier work and serves as a potential model for future localizations and follow-up of repeating FRBs with the uGMRT.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".