A Multi-telescope Campaign on FRB 121102: Implications for the FRB Population
Bibliographic record
Abstract
Abstract We present results of the coordinated observing campaign that made the first subarcsecond localization of a fast radio burst, FRB 121102. During this campaign, we made the first simultaneous detection of an FRB burst using multiple telescopes: the VLA at 3 GHz and the Arecibo Observatory at 1.4 GHz. Of the nine bursts detected by the Very Large Array at 3 GHz, four had simultaneous observing coverage at other observatories at frequencies from 70 MHz to 15 GHz. The one multi-observatory detection and three non-detections of bursts seen at 3 GHz confirm earlier results showing that burst spectra are not well modeled by a power law. We find that burst spectra are characterized by a ∼500 MHz envelope and apparent radio energy as high as 10 40 erg. We measure significant changes in the apparent dispersion between bursts that can be attributed to frequency-dependent profiles or some other intrinsic burst structure that adds a systematic error to the estimate of dispersion measure by up to 1%. We use FRB 121102 as a prototype of the FRB class to estimate a volumetric birth rate of FRB sources Mpc −3 yr −1 , where N r is the number of bursts per source over its lifetime. This rate is broadly consistent with models of FRBs from young pulsars or magnetars born in superluminous supernovae or long gamma-ray bursts if the typical FRB repeats on the order of thousands of times during its lifetime.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".