{
  "id": "AIBD-0018",
  "title": "Convolutional neural network finds 72 previously undetected pulses from fast radio burst FRB 121102 in Green Bank Telescope data",
  "summary": "A Berkeley CNN found 72 unseen pulses from FRB 121102 in Green Bank data, published in ApJ and announced by GBO (Sep 2018).",
  "date_observed": "2018-09-10",
  "date_basis": "unassessed",
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  "account": "On 10 September 2018 the Green Bank Observatory announced a convolutional neural network found 72 previously undetected pulses from repeating fast radio burst FRB 121102. They were in a five-hour, 400-terabyte Green Bank Telescope observation made on 26 August 2017. Gerry Zhang, a University of California, Berkeley graduate student, built it with Breakthrough Listen collaborators. Conventional algorithms had found 21 bursts in the same data. The combined 93 pulses, including 45 within the first 30 minutes, were reported in a peer-reviewed Astrophysical Journal paper (Zhang et al. 2018). They served to search for periodicity. The detections come from a re-analysis of the team's own data. No independent re-detection by another group was found in the sources.",
  "category": "benefit created",
  "unexpected": false,
  "purpose": "Built to detect fast radio burst pulses in Breakthrough Listen radio data that classical search algorithms miss. The 72 bursts were that purpose.",
  "system": "Convolutional neural network for FRB pulse detection (Zhang et al., Breakthrough Listen / Berkeley SETI Research Center)",
  "model_version": null,
  "developer": "University of California, Berkeley (Berkeley SETI Research Center, Breakthrough Listen)",
  "deployer": "Breakthrough Listen, on Green Bank Telescope data",
  "location": "Berkeley, United States",
  "domain": "Astrophysics / radio transients",
  "segment": "Academic research",
  "benefit_type": "Improved Knowledge Discovery",
  "taxonomy_note": null,
  "registry_ids": {},
  "ratings": [
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  "evidence": [
    {
      "kind": "press release",
      "citation": "Green Bank Observatory (2018). AI Uncovers 72 New FRBs in GBT's Breakthrough Listen Data. Press release.",
      "title": "AI Uncovers 72 New FRBs in GBT's Breakthrough Listen Data",
      "url": "https://greenbankobservatory.org/press-release/artificial-intelligence-uncovers-72-new-fast-radio-bursts-in-gbts-breakthrough-listen-data/",
      "date": "2018-09-10",
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      "quote": "the promise it shows for using machine learning to detect signals missed by classical algorithms"
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      "citation": "Zhang, Y. G., Gajjar, V., Foster, G., Siemion, A., Cordes, J., Law, C. and Wang, Y. (2018). Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach. The Astrophysical Journal 866, 149 (arXiv:1809.03043).",
      "title": "Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach",
      "url": "https://arxiv.org/abs/1809.03043",
      "date": "2018-09-09",
      "written_by": "makers",
      "quote": "The detection of 72 new pulses from the repeating fast radio burst FRB 121102"
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      "A long, high-time-resolution radio observation of a known repeater",
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      "Candidate pulses must survive radio-frequency-interference rejection and visual vetting",
      "Independent confirmation would require re-detection by a second pipeline or group"
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  "headline": "Berkeley CNN finds 72 unseen pulses from FRB 121102",
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    "quote": "We report the detection of 72 new pulses from the repeating fast radio burst FRB 121102 in Breakthrough Listen C-band (4-8 GHz) observations at the Green Bank Telescope. The new pulses were found with a convolutional neural network in data taken on August 26, 2017, where 21 bursts have been previously detected.",
    "url": "https://arxiv.org/abs/1809.03043"
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    "note": "No later re-detection or follow-up of these 72 pulses was found in the cited sources.",
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