Classification and recovery of radio signals from cosmic ray induced air showers with deep learning

@article{Erdmann2019ClassificationAR,
  title={Classification and recovery of radio signals from cosmic ray induced air showers with deep learning},
  author={Martin Erdmann and F. Schlueter and Rabiaa Smida},
  journal={Journal of Instrumentation},
  year={2019},
  volume={14},
  pages={P04005 - P04005}
}
Radio emission from air showers enables measurements of cosmic particle kinematics and identity. The radio signals are detected in broadband Megahertz antennas among continuous background noise. We present two deep learning concepts and their performance when applied to simulated data. The first network classifies time traces as signal or background. We achieve a true positive rate of about 90% for signal-to-noise ratios larger than three with a false positive rate below 0.2%. The other network… 
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