FRB 121102 Bursts Show Complex Time–Frequency Structure
Bibliographic record
Abstract
Abstract FRB 121102 is the only known repeating fast radio burst source. Here we analyze a wide-frequency-range (1–8 GHz) sample of high signal-to-noise, coherently dedispersed bursts detected using the Arecibo and Green Bank telescopes. These bursts reveal complex time–frequency structures that include subbursts with finite bandwidths. The frequency-dependent burst structure complicates the determination of a dispersion measure (DM); we argue that it is appropriate to use a DM metric that maximizes frequency-averaged pulse structure, as opposed to peak signal-to-noise, and find DM = 560.57 ± 0.07 pc cm −3 at MJD 57,644. After correcting for dispersive delay, we find that the subbursts have characteristic frequencies that typically drift lower at later times in the total burst envelope. In the 1.1–1.7 GHz band, the ∼0.5–1 ms subbursts have typical bandwidths ranging from 100 to 400 MHz, and a characteristic drift rate of ∼200 MHz ms −1 toward lower frequencies. At higher radio frequencies, the subburst bandwidths and drift rate are larger, on average. While these features could be intrinsic to the burst emission mechanism, they could also be imparted by propagation effects in the medium local to the source. Comparison of the burst DMs with previous values in the literature suggests an increase of ΔDM ∼ 1–3 pc cm −3 in 4 yr; though, this could be a stochastic variation as opposed to a secular trend. This implies changes in the local medium or an additional source of frequency-dependent delay. Overall, the results are consistent with previously proposed scenarios in which FRB 121102 is embedded in a dense nebula.
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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 | 0.001 | 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".