Deep learning for clustering of continuous gravitational wave candidates. II. Identification of low-SNR candidates

Broad searches for continuous gravitational wave signals rely on hierarchies of follow-up stages candidates above a given significance threshold. An important step to simplify these follow-ups and reduce the computational cost is bundle together in single nearby candidates. This called clustering we investigate carrying it out with deep learning network. In our first paper [B. Beheshtipour M. A. Papa, Phys. Rev. D 101, 064009 (2020)], implemented network capable correctly identifying clusters due large signals. this paper, that can detect much fainter These two networks are complementary show cascade achieves an excellent detection efficiency across wide range signal strengths, false alarm rate comparable/lower than methods currently use.