Improving the background of gravitational-wave searches for core collapse supernovae: a machine learning approach

@inproceedings{Cavaglia2020ImprovingTB,
  title={Improving the background of gravitational-wave searches for core collapse supernovae: a machine learning approach},
  author={Marco Cavaglia and Sergio Gaudio and Travis J. Hansen and Kai Staats and Marek Szczepanczyk and Michele Zanolin},
  year={2020}
}
  • Marco Cavaglia, Sergio Gaudio, +3 authors Michele Zanolin
  • Published 2020
  • Physics
  • Based on the prior O1-O2 observing runs, about 30% of the data collected by Advanced LIGO and Virgo in the next observing runs are expected to be single-interferometer data, i.e., they will be collected at times when only one detector in the network is operating in observing mode. Searches for gravitational wave signals from supernova events do not rely on matched filtering techniques because of the stochastic nature of the signals. If a Galactic supernova occurs during single-interferometer… CONTINUE READING

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