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Beheshtipour, B.; Papa, M. A.
Physical review. D, 03/2020, Letnik: 101, Številka: 6Journal Article
In searching for continuous gravitational waves over very many (≈1017) 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 a very low false alarm rate and maintains a reasonable detection efficiency for signals with lower amplitudes, i.e., at ≲ current upper limit values.
