Detection of Bursts from FRB 121102 with the Effelsberg 100 m Radio Telescope at 5 GHz and the Role of Scintillation
Bibliographic record
Abstract
Abstract FRB 121102, the only repeating fast radio burst (FRB) known to date, was discovered at 1.4 GHz and shortly after the discovery of its repeating nature, detected up to 2.4 GHz. Here, we present three bursts detected with the 100 m Effelsberg radio telescope at 4.85 GHz. All three bursts exhibited frequency structure on broad and narrow frequency scales. Using an autocorrelation function analysis, we measured a characteristic bandwidth of the small-scale structure of 6.4 ± 1.6 MHz, which is consistent with the diffractive scintillation bandwidth for this line of sight through the Galactic interstellar medium (ISM) predicted by the NE2001 model. These were the only detections in a campaign totaling 22 hr in 10 observing epochs spanning five months. The observed burst detection rate within this observation was inconsistent with a Poisson process with a constant average occurrence rate; three bursts arrived in the final 0.3 hr of a 2 hr observation on 2016 August 20. We therefore observed a change in the rate of detectable bursts during this observation, and we argue that boosting by diffractive interstellar scintillations may have played a role in the detectability. Understanding whether changes in the detection rate of bursts from FRB 121102 observed at other radio frequencies and epochs are also a product of propagation effects, such as scintillation boosting by the Galactic ISM or plasma lensing in the host galaxy, or an intrinsic property of the burst emission will require further observations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.000 |
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".