Multiwavelength Radio Observations of Two Repeating Fast Radio Burst Sources: FRB 121102 and FRB 180916.J0158+65
Bibliographic record
Abstract
Abstract The spectra of fast radio bursts (FRBs) encode valuable information about the source’s local environment, underlying emission mechanism(s), and the intervening media along the line of sight. We present results from a long-term multiwavelength radio monitoring campaign of two repeating FRB sources, FRB 121102 and FRB 180916.J0158+65, with the NASA Deep Space Network (DSN) 70 m radio telescopes (DSS-63 and DSS-14). The observations of FRB 121102 were performed simultaneously at 2.3 and 8.4 GHz, and spanned a total of 27.3 hr between 2019 September 19 and 2020 February 11. We detected two radio bursts in the 2.3 GHz frequency band from FRB 121102, but no evidence of radio emission was found at 8.4 GHz during any of our observations. We observed FRB 180916.J0158+65 simultaneously at 2.3 and 8.4 GHz, and also separately in the 1.5 GHz frequency band, for a total of 101.8 hr between 2019 September 19 and 2020 May 14. Our observations of FRB 180916.J0158+65 spanned multiple activity cycles during which the source was known to be active and covered a wide range of activity phases. Several of our observations occurred during times when bursts were detected from the source between 400 and 800 MHz with the Canadian Hydrogen Intensity Mapping Experiment (CHIME) radio telescope. However, no radio bursts were detected from FRB 180916.J0158+65 at any of the frequencies used during our observations with the DSN radio telescopes. We find that FRB 180916.J0158+65's apparent activity is strongly frequency-dependent due to the narrowband nature of its radio bursts, which have less spectral occupancy at high radio frequencies (≳ 2 GHz). We also find that fewer or fainter bursts are emitted from the source at high radio frequencies. We discuss the implications of these results for possible progenitor models of repeating FRBs.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".