Deep learning for clustering of continuous gravitational wave candidates II: identification of low-SNR candidates

@article{Beheshtipour2020DeepLF,
  title={Deep learning for clustering of continuous gravitational wave candidates II: identification of low-SNR candidates},
  author={B. Beheshtipour and Maria Alessandra Papa},
  journal={ArXiv},
  year={2020},
  volume={abs/2012.04381}
}
In searching for continuous gravitational waves over very many ($\approx 10^{17}$) templates , clustering is a powerful tool which increases the search sensitivity by identifying and bundling together candidates that are due to the same root cause. We implement a deep learning network that identifies clusters of signal candidates in the output of continuous gravitational wave searches and assess its performance. For loud signals our network achieves a detection efficiency higher than 97\% with… 
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